Left atrial (LA) functional analysis has an established role in assessing left ventricular diastolic function. The current standard echocardiographic parameters used to study left ventricular diastolic function include pulsed-wave Doppler mitral inflow analysis, tissue Doppler imaging measurements, and LA dimension estimation. However, the above-mentioned parameters do not directly quantify LA performance. Deformation studies using strain and strain-rate imaging to assess LA function were validated in previous research, but this technique is not currently used in routine clinical practice. This review discusses the history, importance, and pitfalls of strain technology for the analysis of LA mechanics. The left atrium modulates left ventricular filling and cardiac performance through its roles as a reservoir –3, conduPatients with diabetes and normal LA size have impaired LA deformation mechanics . AdditioThis paper explains the application of these novel techniques to assess LA function and critically discusses the pitfalls, problems, and impacts of these noninvasive imaging techniques. This review also explains how LA deformation assessments in routine clinical practice may facilitate appropriate AF management strategies and guide treatments to prevent AF. “blood enters the ventricles… by the beat of the auricles” and “… they are filled as reservoirs” [William Harvey discussed the important role of the auricles in 1628:ervoirs” . A youngervoirs” . Contrarervoirs”  laid theervoirs” , and Henervoirs” , suggestervoirs”  describeervoirs”  publisheervoirs”  examinedervoirs” , who dirervoirs” . The relervoirs” . The conervoirs”  using voervoirs”  concludeervoirs” . The norervoirs” , leadingervoirs” . The hemervoirs” , 37. Theervoirs”  documentervoirs” . In 1991ervoirs”  and 1997ervoirs” , Thomas ervoirs”  and the Echocardiography provides a broad range of information on anatomic and functional changes to heart structures over time , 43. TwoUsing conventional 2D echocardiography, Saraiva et al.  obtainedDiastolic disease was already clinically recognized in the early 1980s , 57, 58 Vmax E = passive inflow) and a comparatively higher atrial contraction velocity (Vmax A = active inflow) are established signs of diastolic dysfunction [p is the density of blood (p = 1.06 g/cm3) and the units of force are measured in g-cm/s−2 or dynes.A lower peak early diastolic velocity  and a′ (A′) derived from TDI  earlier. Hayashilateral as the best index to detect diastolic dysfunction in patients with heart failure and a normal ejection fraction (EF); Ommen et al. [Kasner et al.  did not n et al.  suggesteMullens et al.  suggesteGalderisi et al.  recommenBhella et al.  made a rDespite the reliability of TDI , problemAs a whole, the heart acts as a suction pump, but the atrium represents an important component of a functioning cardiovascular system . The musDi Salvo et al.  measuredε) curve as indicators of LA function: contractile function from 0.1 to 0.2 seconds, reservoir function from 0.3 to 0.5 seconds, and conduit function from 0.5 to 0.7 seconds  or strain-rate curves exists during the time intervals of ECG intervals. Whether septal atrial wall or only “outside” mobile walls  should be considered remains unclear. Therefore, the possibility of introducing error exists using the segmental strain of the LA to estimate global strain values. Kokubu et al. [The possibility for different estimations of “peak” values or time periods using strain  and the regional LA strain rate (LAε′). The interobserver variability of global values was 5.7% for velocity and 6.5% for strain. A total of 13 LA regions, 5 regions adjoining the mitral annulus, and 5 regions in the midatrial wall were examined; in each view, the superior, or “roof,” region, corresponding to the area encompassing the region between the 4 pulmonary veins, was also examined [Kim et al.  proposedexamined . This paε positive peak, ε negative peak, and ε total (ε = strain (%)) were the suggested values. This working group suggested the following strain rate values: late negative peak strain rate (SRlate  neg  peak), positive peak strain rate (SRpos  peak), and early negative peak strain rate (SRearly  neg  peak). The global LA negative strain (LAε) and global LA SR late negative peak were not correlated with the active LA stroke volume or active LA emptying function [Saraiva et al.  suggestefunction .Additionally, an assessment of the electromechanical delay (ca. 60 ms) between the interatrial septum and lateral wall was proposed .Additional research groups , 104–106Speckle tracking was used to evaluate atrial function in different patient groups, including those with hypertension , 21, 107LA), early diastolic strain (conduit function = ELA), and active atrial contraction (ALA) were used in a pilot study prior to pulmonary vein ablation. The described parameters exhibited sufficient intraobserver variability .Schneider et al. suggested that atrial strain and strain rate values of the atrial septum might predict sinus rhythm maintenance after AF ablation. In 2014, Spethmann et al. showed similar results in their study . They suP = 0.001) in patients with mitral regurgitation and indications for mitral surgery compared with controls [Severe mitral regurgitation is associated with LA dysfunction related to the presence of indications for mitral surgery. LA dysfunction measured using reservoir strain may be a valuable clinical marker for follow-up and decision making in conventional mitral surgery . The rescontrols .Diminished augmentation of the LA reservoir and passive emptying functions during dobutamine stress were strongly associated with cardiovascular events . AssessmP = 0.0005).Hammerstingl et al. described reduced global longitudinal atrial strain as a predictor of AF recurrence . In a 4-Strain imaging  is the mAll current software options were designed to conduct left ventricle analyses; less software is available for atrial strain analyses. There is also a lack of standards or official consensus documents. The underlying problems are the theoretical presence of three segments, at a minimum, which can be placed in different positions and extensions or the analysis of six segments in different echo views . DiffereThe four-chamber view (the most commonly used) provides atrial septal movement, which may influence the analyses as a whole in an unclear manner. Other issues include the relatively small “cut-off” values or overlapping areas for differential diagnoses or disease stages . We haveThe development of a standardized software tool for the specific analysis of LA function and consequent experimental studies using the standardized parameters  are needed. The measurement onset and time points must be standardized . Evaluations of intra- and interobserver variability according to the ventricular strain are required for all parameters . The atr


Z2/r = 18), has the remarkable capability to both (1) aggregate and compact Aβ42 peptide monomers into higher order, more neurotoxic oligomeric, and fibrillar structures, and (2) impair, at the molecular-genetic level, the cellular machinery responsible for Aβ42 peptide monomer phagocytosis and clearance from the cell  is probably the most intensively studied brain cell protein in neurobiology. βAPP is processed by tandem beta-gamma secretase cleavage into 42 amino acid amyloid (Aβ42) peptides, whose progressive accumulation is one distinguishing feature of Alzheimer’s disease (AD) neuropathology –3. Whilethe cell . This op4)2.12H2O], which is used worldwide as a clarifying agent in water purification, reacts with impurities. When added to turbid drinking water, aluminum crosslinks organic impurities, allowing them to flocculate or “stick together” and precipitate out of solution, resulting in a highly clarified and esthetically pleasing “finished” water product , highly expressed in human neurons has been implicated as a regulator of neuronal cytoarchitecture, synaptic plasticity, axon guidance, and cell–cell interactions in the brain and retina –3. Via t product . Interesposition . In partposition , 16–20. position , 22.Active microglial cell-mediated phagocytic processes that remove excessive, neurotoxic, or end-stage molecules from the brain are a naturally occurring mechanism to cleanse the neural environment and maintain neural homeostasis –11. FailTaken together, these results strongly suggest that one of the most prominent features of AD – the progressive accumulation and aggregation of Aβ42 peptides into senile plaques – is driven by aluminum via multiple interdependent pathogenic mechanisms. These findings continue to support an active role for aluminum in key neuropathogenic, inflammatory, and amyloidogenic pathways that contribute to the AD process. Aluminum appears to therefore drive AD-relevant amyloidogenic pathology (1) directly, by aggregation of Aβ42 peptide monomers into higher order structures that subsequently form into senile plaque cores, and (2) indirectly, through an NF-kB- and miRNA-34a-mediated epigenetic mechanism that contributes to a down-regulation in the expression of the key phagocytosis sensor protein TREM2, and a failure of microglial cells to naturally sense, phagocytose, and eliminate neurotoxic Aβ42 peptides. Hence, both of these pathways have strong potential to contribute, perhaps cooperatively, to the failure to adequately phagocytose naturally generated Aβ42 peptide monomers, thus promoting their aggregation and driving amyloidogenesis with pro-inflammatory consequences. Indeed, the aluminum-mediated aggregation of Aβ42 peptide monomers into higher order structures of higher molecular mass may preclude them from being adequately “ingested” by microglial cell-mediated phagocytic mechanisms, further supporting their accumulation and self-association in the extracellular space. It will certainly be interesting to see if aluminum salts perform similar pathogenic roles in other progressive, age-related neurodegenerative disorders of the CNS with an innate-immune, inflammatory, and/or amyloidogenic component.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Chronic widespread pain (CWP) is common and associated with prominent negative consequences. The aim of this study was to assess the prevalence of persistent CWP in an 11-year prospective cohort study in the general population, and to examine anxiety, depression, alcohol use, poor sleep, body mass index (BMI) and chronic disease, along with demographic, lifestyle and other health-related variables as possible predictors for the assumed CWP persistence.CWP was defined as having pain at three or more predefined sites (involving the trunk and upper and lower limbs) for at least three months in the last year. We used a Norwegian general population cohort of 28,367 individuals who responded to both the second (1995–1997) and the third (2006–2008) waves of the Nord-Trøndelag Health Study . Data were analysed with logistic regression models.CWP prevalence in HUNT2 was 17%. Of those reporting CWP in HUNT2, 53% still reported CWP at follow-up in HUNT3. Adjusted analyses revealed that depression and alcohol consumption were not substantially associated with the 11-year prospective CWP outcome. Poor sleep, obesity and chronic disease predicted persistent CWP, and being male and/or 60 years or older was protective.This cohort study revealed that nearly half of the participants with baseline CWP resolved from CWP 11 years later. Among those whose CWP did not resolve, obesity, sleeping problems and chronic disease predicted CWP persistence, while aging and male sex was protective. Anxiety, mixed anxiety and depression, former smoking, and overweight were weakly associated, while depression, moderate exercise, and alcohol use were not associated with persistent CWP. Chronic pain is common in the general population with a prevalence ranging from 20% to 55% -5. ChronCross-sectional studies have demonstrated that different pain characteristics are interrelated ,22. TheyA few population-based prospective studies have examined predictive factors of CWP persistence associated with CWP prevalence, suggesting that some 35% of those with initial CWP, are likely to experience persistence when they are females, of older ages, or exhibit additional physical or psychological symptoms ,31. In a2 are predictors of CWP persistence and that (ii) young age, male sex, alcohol consumption and moderate exercise are protective factors.The aim of this study was to 1) assess the prevalence, and 2) analyse possible predictive health-related, lifestyle and demographic factors as long-term predictive factors of CWP persistence. We hypothesized that (i) anxiety, depression, poor sleep, smoking and BMI ≥ 25 kg/mThis study is based on a large representative Norwegian cohort of individuals attending the second and third waves of the Nord-Trøndelag Health Study . The HUNT study (“Helseundersøkelsen i Nord-Trøndelag”), designed as a longitudinal cohort study consisting of three health surveys, was carried out three times at 11 year intervals, in which all residents aged 20 years and older in Norway’s Nord-Trøndelag County were invited to participate. The first survey (HUNT1) was conducted between 1984 and 1986, while HUNT2 and HUNT3 were performed in 1995–1997 and 2006–2008, respectively. HUNT1 was designed primarily to cover four sub-studies regarding hypertension, diabetes, lung diseases and quality of life , while tThis study includes those 20 years and older in age  who attended both HUNT2 and HUNT3 . Of thosThe chronicity of musculoskeletal pain was determined by the participants responding positively with a “yes” on the following question from the validated Standardized Nordic Questionnaire (SNQ): “During the last year, have you had pain and/or stiffness in your muscles and limbs that has lasted for at least 3 consecutive months?” . Those rThe independent variables were sex and baseline information on age, separate anxiety and depression measures from the Hospital Anxiety and Depression Scale (HADS), alcohol use, insomnia and body mass index (BMI). Variables also included smoking status, marital status, education, exercise, and chronic disease, all of which were observed in the HUNT2 period. HADS is a well-established and validated 14-item, self-rating questionnaire that aims to detect general symptoms of anxiety and depression. It comprises seven items for depression (HADS-D) and seven for anxiety (HADS-A), in which each item includes a four-point Likert-scale response category (0–3) ,41. A mi2), normal (BMI 18.5–24.9 kg/m2), overweight (BMI 25–29.9 kg/m2) and obese (BMI ≥ 30 kg/m2). Smoking was identified by using a constructed variable of smoking status categorized into “never smoking”, “previous smoking” and “current smoking”. Data on marital status and age were provided from the National Population Registry. Marital status was categorized into two groups: “single/divorced/separated/widower” and “married/cohabitant/partnership”. Education level was specified in three categories: “primary school”, “high-school” and “university/college of four years or more”. Physical exercise was measured through two variables of light and hard duration as: “average of hours of both light and hard physical activity per week in the last year” and reflected “no” up to “moderate” levels of physical activity. Long-term illness (chronic disease) was evaluated by the question “do you suffer from any long-term illness or injury of a physical or psychological nature that impairs your functioning in everyday life?” where “long term” means at least one year. The response options were “yes/no”. The “no pain” group in the study population covered all subjects that did not satisfy the CWP criteria, including those that responded “yes” to the introductory question on pain but did not indicate the site of pain. The sex ratios were calculated by dividing female prevalence by male prevalence.The influences that sleeping problems had on the CWP outcome were examined by using three questions from Q2, each related to non-restorative sleep, difficulties of sleep onset, and problems of maintaining sleep. Non-restorative sleep was identified by asking “how often do you suffer from insomnia?”, where the response options included “never or a few times a year”, “1–2 times a month”, “about once a week” and “more than once a week”. Problems of sleep onset and maintaining sleep were measured by two questions: “Have you had difficulty falling asleep in the last month?” and “during the last month, have you woken too early and not been able to get back to sleep?” Response options included “almost every night”, “often”, “now and again” and “never”, where the responses “almost every night” and “often” were defined as problems (1) and “now and again” and “never” as no problems (0). The three variables of “non-restorative sleep”, “sleep onset” and “maintaining sleep” were combined into one variable reflecting sleeping problems and categorized as “no problem” or “problem” (i.e. reporting 1 or more sleeping problems on the 3 items). According to the cut-offs recommended from the World Health Organization’s Global Database on Body Mass Index, , BMI wasTwo models were used to examine predictors of CWP persistence. The examination of each was performed through logistic regression analyses resulting in odds ratios, with 95% confidence intervals. Model 1 captured the results from each variable of interest in a crude age- and sex-adjusted analysis. In model 2, all variables were included in one multivariable model. Because some variables were missing observations, only complete cases were included in the regression analyses. Missing observations concerned 1,157 respondents (23%) from the baseline sample. The analyses were examined for statistical interactions between sex and the independent variables. All data were analysed by using Stata 12.1 for Windows .This study was approved by the Board of Research Ethics in Health Region IV of Norway and the National Data Inspectorate.Of the 28,367 subjects who completed the introductory question on chronic musculoskeletal pain, 28,313 subjects were included in HUNT2 and 27,574 were included in HUNT3. The overall mean age in the HUNT2 cohort was 50.1 years (SD 17.2), ranging from 19.1 to 101.1 years, while the mean age in the HUNT3 cohort was 53.1 years (SD 16.1), ranging from 19.0 to 100.8 years (data not shown). The mean age in the baseline sample (CWP in HUNT2) was 52.3 years (SD 11.4), varying between 19.5 to 85.9 years. The age distribution frequency of the baseline sample showed that the majority of the participants (59%) were aged 40 to 59 years. The mean baseline HADS depression and anxiety scores were 4.42 (SD 3.32) and 5.50 (SD 3.7), respectively, versus 3.49 (SD 3.1) and 4.24 (SD 3.4), respectively, in the study population (data not shown). Descriptive data on the variables of interest are described in Table The mean HADS scores in the HUNT2 study population were similar to the mean HADS scores in the HUNT2 cohort. Only 0.4% of the study population reported chronic musculoskeletal pain without specifying any pain location.Of those reporting CWP in HUNT2 (i.e. baseline = 17%), 53%  still reported CWP in the HUNT3 follow-up, and 74% of these were females. By comparison, the overall female proportion in the study population was 57%.From the health-related variables in the unadjusted analysis , while current smokers differed only marginally from never smokers . Compared with study participants with normal weight, obese participants had higher odds of CWP persistence . Drinking alcohol 8 times or more a month  showed a non-substantial protective tendency when compared with abstainers. Participants 60 years or older had a lower odds of CWP persistence  compared with the youngest age group (age 20–39). Also, those with an education at the university/college level had a lower odds of CWP persistence  than those with a primary education only. Males had about half the odds of CWP persistence  compared with females.In the adjusted analysis, symptoms of anxiety  and mixed anxiety and depression  only indicated a weak increase in CWP persistence. Sleeping problems remained a substantial predictor of CWP persistence , compared with the lack of sleeping problems. Those with a chronic disease had a 75% increased odds of CWP persistence (OR: 1.75. 95% CI: 1.53–2.01) compared with participants without a chronic disease. Adjusted for the other possible predictors, overweight participants had a weak increased odds of CWP persistence  while obese participants had a 66% increased odds of CWP persistence  compared with normal weight individuals. Former smokers had a weak increase in CWP persistence  compared with never smokers. Compared with the youngest age group (age 20–39), study participants 60 years or older showed a reduced odds of CWP persistence , and males had about half the odds of CWP persistence  compared to females. All results, both crude and adjusted models, are presented in Table Some participants experienced CWP in HUNT2, but did not attend HUNT3 . To obtain descriptive measures, these HUNT3 non-participants were compared to the HUNT3 participants who had CWP in HUNT2, i.e. the baseline sample . The mean age of non-participants was 54.4 years (SD 15.7). Compared to the baseline sample, non-participants were more likely to be obese, have sleeping problems and smoke daily. There were also group differences in age distribution, education, marital status and chronic disease. The results are presented in Table Statistical interaction analyses indicated weak evidence of statistical interaction between sex and the other evaluated variables (p > 0.12).In this large prospective cohort study, 53% of the participants with baseline CWP still had CWP at follow-up. According to the adjusted model, we found strong positive associations over time between persistent CWP and sleeping problems, being obese and having a chronic disease, while anxiety, mixed anxiety and depression symptoms, former smoking and being overweight showed weaker positive associations with persistent CWP 11 years later. Being a male and being 60 years of age were substantial protective factors against long-term persistent CWP.A major strength of this study was its large population base, its acceptable participation rate and its long-term follow-up. The study also contained a robust design and a lot of variables for comparing between different follow-up times. The pain measures were gauged with validated, well-known and standardized questionnaires that rely on self-reporting , which aDefining chronic pain only by duration and location, but not by pain intensity or severity may weaken the study’s optimality. In epidemiologic studies of pain, which are often based on self-report questionnaires rather than clinical findings, the complex nature of chronic pain represents a major challenge for the study’s validity. Another weakness is that the participation rate decreased in the last HUNT study, as it does in most longitudinal population-based cohort studies. The attrition was 15% and was most pronounced among males and younger adults. A non-participant study based upon the HUNT2 study revealed that being abroad and the lack of time for scoring were the main reasons for non-attendance for people aged 20–44 years . DecreasAlthough this rather large study indicates that CWP occurs frequently in the general population, the conditions within CWP do not necessarily appear as invariable or unchanging, and with time, the individuals could move through various categories of chronic pain syndrome . In thisYet, a substantial number of subjects at baseline 47%) changed from having CWP at baseline to not having CWP at follow-up. The fact that a large proportion of the general population actually does resolve from CWP is additional knowledge for pain research and treatment. This finding is in contrast with other studies showing that the overall prevalence of CWP is stable over time and that pain is likely to persist if accompanied by, for example somatic symptoms and older age ,32. Our % changedDepression and anxiety disorders are commonly reported co-morbid conditions in CWP ,47,54-57The results demonstrated that many respondents (53%) in the general population maintained CWP, but a large proportion (47%) also resolved within an 11-year period. Persistent CWP was examined in association with important cofactors suggested by previous research. The study revealed strong positive associations over time with sleeping problems, obesity and chronic disease, while being 60 years or older was protective. Contrary to other studies, depression, anxiety and the frequency of alcohol consumption were not substantial predictors of outcome. Except from the sex differences in prevalence, the adjusted analyses revealed no prominent sex differences related to the predictors or protectors of CWP persistence. This large prospective population-based study brings new knowledge about what is important for long-term CWP persistence. Additional prospective population studies could reveal predictive factors for why many CWP individuals recover and why others do not recover from pain.The authors declare no conflict of interest.IM was responsible for collecting and analysing data and manuscript drafting. RWG, OML and EAF contributed to the study’s conception, as well critical revision and manuscript drafting. JHB was involved in the data analysis and statistical interpretation, and contributed in particular with methodical and epidemiological support and critical revision and manuscript revising and drafting. All authors have made substantial intellectual contributions and read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2474/15/213/prepub


The apolipoprotein E (APOE) e4 allele is strongly associated with increased risk of cognitive impairments in older adulthood. There is also a possible link to enhanced cognitive performance in younger adults, and the APOE e4 allele may constitute an example of antagonistic pleiotropy. The aim of this work was to investigate the cognitive and neural  effects of the APOE e4 allele during mid-age (45–55 years), where a transition toward cognitive deficit might be expected. APOE e4 carriers (e4+) were compared with non-e4 carriers (e4−) on tasks of sustained and covert attention and prospective memory, and functional magnetic resonance imaging data acquired. Performance by e4+ was equivalent or better than e4− on all 3 tasks, although performance benefits were less pronounced than in youth. Neurally, e4+ showed less task-related recruitment of extrastriate and parietal areas. This became more evident when neural activation data were compared with that of young adults acquired in a parallel study. As expected, mid-age participants showed more diffuse neural activation. Notable was the fact that e4+ showed a relative inability to recruit parietal regions as they aged. This was coupled with a tendency to show greater recruitment of frontal regions, and underactivation of extrastriate visual regions. Thus, mid-age e4+ show a pattern of neural recruitment usually seen later in life, possibly reflecting the source of an accelerated aging profile that describes the e4 genotype. The e4 In spite of the negative consequences associated with the e4 allele in later life, there is some evidence that paradoxically the e4 allele may confer certain cognitive advantages in youth , and theImaging techniques have also been used to examine neural differences in e4+ at mid-age. Using positron-emission tomography, cognitively normal e4+ aged 50 to 65 years have been shown to have abnormally low cerebral metabolic rates for glucose in brain regions where AD patients also show reductions in metabolism; these controls also show widespread reductions in metabolic rate across prefrontal regions, above and beyond that seen in AD . This coIn earlier work, we explored neural activation patterns and performance differences in young adult e4+ and e4−. In the 18–28 years age range, we showed that e4+ can manifest an advantage on specific cognitive measures. Specifically, we reported that e4+ generated more words in the early stages of a verbal fluency task, and were faster at the ongoing component of a prospective memory (PM) task . e4+ outIn the present work our principle aim was to extend these investigations into a mid-age cohort of e4+ and e4−, using a narrow age range of 45–55 years. We used a battery of cognitive tasks that included measures of attention and PM, for some of which fMRI data were acquired. Because many studies of APOE and cognition have used tasks that specifically target the medial temporal lobe (MTL) function, we chose tasks that instead recruit frontal and parietal regions, to investigate effects of APOE in regions beyond the MTL. Using our published data from young adults  we carri22.12.1.1Healthy young participants (98) were recruited , and healthy middle-aged participants (78) were recruited , all right-handed. Volunteers were excluded from the study for untreated high blood pressure, cardiac pathology, a history of psychiatric or neurologic illness, current use of psychoactive medication, and presence of metallic implants including bridges and braces, or tattoos above the shoulder. All participants were non-smokers (and had been for at least 5 years), had a body mass index within the normal range and had English as their first language.www.kbioscience.co.uk), using their own system of fluorescence-based competitive allele-specific polymerase chain reaction (KASPar). Two APOE single-nucleotide polymorphisms (SNPs) rs429358 and rs7412 allowed identification of the three major APOE alleles .Initial screening involved signing of written informed consent , and cheek swab samples were collected for DNA analysis from each participant. APOE genotypes were determined by KBiosciences . Demographics are shown in 2.22.2.1The National Adult Reading Test, NART  estimate2.2.2Immediate free recall provides an episodic memory score. Participants are presented with 20 unrelated words at a rate of 1 word every 2 seconds in a computerized sequence; they are then prompted for immediate written recall.2.2.3The 6-minute RVIP task based on  is a com2.2.4The ongoing task involved simply sorting computerized images of 52 regular playing cards displayed in random sequential order on-screen. Card faces were displayed for 1 second, after which the card back was displayed for 2 seconds plus a variable jitter between 0.1 and 1 second . Using a 4 button-box in their right hand, volunteers were instructed to press button 1 for HEART cards, button 2 for SPADES , and make no response to CLUBS or DIAMONDS . Volunteers were instructed to respond as quickly as possible. At each of the scanning sessions, volunteers practiced the ongoing sort task before entering the scanner, and were then additionally given the prospective memory instruction: they were asked to respond by pressing button 3 for any occurrence of a number “7” card independent of suit (the PM intention). Thus, when in the scanner, participants performed the ongoing task as practiced, but with the additional PM instruction. Presentation of any “7” card constituted a PM trial. Within each scanner session, each volunteer sorted 8 decks of cards with the PM intention over a total period of approximately 15 minutes. Thus, there were a total of 416 trials, of which 32 were PM trials, 192 were “sort” trials and 192 were “withhold” trials. Accuracy and reaction times (RT) to sort and PM trials were recorded.2.2.5The CA task based on  is a com2.3Recalled volunteers attended 3 sessions. The first session comprised baseline measures of IQ (NART) and episodic memory . These were followed by the RVIP task. Finally, participants were familiarized with the CA task. In 2 subsequent scanning sessions (approximately 1 week apart), volunteers participated in a double–blind pharmacologic manipulation, in 1 session self-administering placebo and in the other, nicotine , 18–20 minutes before imaging. The sessions were identical and their order randomized and counterbalanced.The pharmacologic manipulation was designed to explore the effects of nicotine administration on performance, and is reported in a separate paper . In this2.4Task analyses were completed using data from the placebo sessions only; nevertheless, ANOVA included order of sessions  as a factor.2.4.1Number of correct detections, average latency to correct detections and the number of false alarms (responses to nontargets) were analyzed separately using ANOVA. Time bin (6 levels: minutes 1–6) was the within-subject factor; genotype  the between subject factors.2.4.2Accuracy and RT data were analyzed for PM and for ongoing trials. ANOVA examined effects of genotype  and session order (2 levels: first or second scanner session) in a mixed design.2.4.3The “validity effect” is the RT cost associated with the presence of an incongruent cue; it is measured by the difference between mean RTs to the incongruent and congruent conditions. Preliminary ANOVA examined effects of cue-target interval ; there were no effects or interactions related to cue-target interval, and so data were collapsed across this factor, for simplicity. Thus, ANOVA involved genotype  and session order (2 levels: first or second scanner session) in a mixed design.2.5fMRI datasets sensitive to BOLD contrast were acquired at 1.5 T. Standard preprocessing steps were applied; fMRI data were analyzed with the standard hierarchal model approach used in SPM8. Further information can be found in the p < 0.05 FWE-corrected. Small volume corrections,  are also reported at p < 0.05 FWE-corrected. A priori regions of interest included areas where differences between e4+ and e4− have been reliably demonstrated . Regions of interest were defined using the Wake Forest University PickAtlas. Anatomic localization of clusters was performed using the Talairach Daemon , and the anatomy toolbox for SPM , with e4+ scoring more hits. There was also a main effect of time  and a time by genotype interaction .There was no effect of age, and no age by genotype interaction. There was a trend toward a main effect of genotype , with young e4+ responding faster than e4−, and mid-aged e4+ responding slower than e4−.There were no effects of age or genotype. There was a trend toward an age by genotype interaction  with e4+ making fewer false alarms. There was no age by genotype interaction.There was no main effect of age. There was a trend toward a main effect of genotype  with mid-age participants being slower. There was also a main effect of genotype , with e4+ being slower than e4−. There were no interactions or effects of session order.On accuracy there were no effects of age or genotype. On RTs, there was a main effect of age , with mid-age e4+ detecting more, and mid-age e4− detecting less, relative to the young adult group. There was also a main effect of session order , with accuracy higher in session 2 , but no interactions. On RTs, there was a main effect of age  with mid-age participants being slower. There was also a main effect of genotype , with e4+ being slower. There were no interactions.On accuracy, there were no effects of age or genotype. There was an age by genotype interaction  and 3 mid-age volunteers were excluded from analysis  for not performing the task correctly. After these exclusions, remaining volunteers exceeded 90% correct performance .p = 0.001), with mid-age participants showing a larger validity effect. There were no main effects of genotype or session order, and no interactions. Examining the raw data pointed to a possible outlier in the mid-age group, whose reaction times to incongruent trials were more than 3 standard deviations higher than the mean for the mid-age group. Excluding this participant, the ANOVA demonstrated a significant main effect of genotype , with e4+ showing a smaller validity effect.On this task there was a main effect of age , reflecting a decreasing hit rate over the 6 minutes of the task. There was a time by genotype interaction . During minute 2, e4+ scored significantly more hits than e4− .3.2.1.2p = 0.89), no time by genotype interaction , and no significant difference in reaction time between e4+/e4− .There was no main effect of time on latency  completed the RVIP but did not proceed to the imaging phase of the study. Summary data are shown in 3.2.2.1p = 0.018). There were no effects, or interactions with, session order.There were no genotype effects on accuracy. On reaction times, e4+ were significantly slower than e4− . There was a significant effect of session order  with accuracy higher in session 2  but no interactions. On reaction times, e4+ were significantly slower than e4− . There were no effects of, or interactions with, session order.e4+ were significantly more accurate than e4− . There was no effect, or interactions with, session order.The validity effect was analyzed by genotype and session order. ANOVA revealed no main effect of genotype  and right IPC , see p < 0.001 FWE-corrected, k = 536), left parahippocampus (subiculum) , and right IPC . In all cases, effects were driven by greater activity in mid-age participants. There were no main effects of genotype, and no age by genotype interactions.Across all trial types, a main effect of age was seen in right Area 6  and in right SPL . An active cluster was also present in left SPL  although not significant at p < 0.05 FWE-corrected. In both cases, effects were because of reduced activity in e4+.Across all trial types  there were no main effects of genotype, and no interactions between genotype and trial type. On PM trials only, a main effect of genotype was present in extrastriate cortex  and (mid PM < youngs PM) were constructed separately for e4− and e4+, and then used as exclusive masks to isolate activity that was genotype-specific.p = 0.034 FWE-corrected, k = 172) and left parahippocampus (CA) . Activity was also present in left orbitofrontal cortex , On PM trials, the contrast (e4+ mid PM > e4+ youngs PM) masked with (e4− mid PM > e4− Youngs PM) revealed activity specific to e4+ in left inferior frontal gyrus , The opposite contrast (e4+ mid PM < e4+ youngs PM) masked with (e4− mid PM < e4− youngs PM) revealed activity specific to e4+ in left superior parietal  but not for e4− . There was no significant difference between the r-values of these 2 correlations, using a Fisher r-to-z transformation . There was no correlation in either genotype with PM RT. In parahippocampus and left superior parietal, there were no correlations with PM accuracy or RT.To investigate the significance of the genotype-specific neural activations described previously, activation intensities specific to PM trials were extracted for each mid-age participant in left inferior frontal gyrus, left parahippocampus, and left superior parietal using the coordinates of peak activation identified previously. In left inferior frontal gyrus, activation correlated with PM accuracy for e4+ . Applying the contrast e4− > e4+ to the modulation revealed activity in extrastriate cortex . Applying the reverse contrast (e4+ < e4−) did not show any effects.In a separate analysis, the reaction time for each Sort and PM trial was included as a parametric modulator, and modeled as a separate column in the design matrix. A significant main effect of modulation by PM reaction time was observed in left Area 6 , right cerebellum , left cerebellum , right inferior frontal , and left SMA , Neural activity relating to the validity effect was analyzed by contrasting incongruent and congruent conditions. A main effect of age was seen in left Area 6, extending into left inferior and superior parietal lobules  and (mid < youngs) were constructed separately for e4− and e4+. When results for e4+ were then masked with that of e4− to determine where age-related differences in activity occur in e4+, but not e4−, no significant findings emerged.Results for e4− were then masked with that of e4+ to determine where age-related differences in activity occur in e4−, but not e4+.p < 0.001 FWE-corrected, k = 90), left V5/V5 , right cerebellum , left IPC , and left SPL , The contrast (e4− mid > e4− young) masked with (e4+ mid > e4+ youngs) revealed activity specific to e4− in left area 6  masked with (e4+ mid < e4+ youngs) revealed no activity.4In this study, we investigated cognitive performance in mid-aged e4+ and e4− volunteers, and genotype differences in neural activation patterns between youth and mid age individuals. We used tests of sustained and covert attention and prospective memory. Contrary to cognitive performance impairments reported in some earlier studies that had used a much wider age range than we used , we founOn the sustained attention (RVIP) task, mid-aged e4+ outperformed e4− at the trend level. These e4+ advantages were not as pronounced as those we have previously reported in the young adult group, where e4+ outperformed e4− across each minute of the task . InteresOn the covert attention task, performance levels were no different between mid aged e4+ and e4−. This again contrasts with young adult performance on this task, in which we have reported a reduced validity effect for e4+, and increased parietal activity on both congruent and incongruent trials . At mid In the PM task, e4+ were significantly slower on both the ongoing task and PM trials, while showing a trend toward greater accuracy. Neural differences were observed on PM trials, with mid aged e4+ showing less activity in extrastriate and parietal regions, relative to e4−.The antagonistic pleiotropy hypothesis would suggest a transition point for e4+ as they move from being cognitively advantaged in young adulthood to cognitively disadvantaged in older adulthood . The eviA number of imaging studies have explored APOE-related neural differences across the life span. Young adult e4+ show enhanced resting state activations and greater hippocampal activity during encoding memory tasks , as wellTo investigate neural changes from youth to mid-age, we contrasted fMRI data from our mid age cohort with that acquired in a group of young adults under an identical protocol . In bothinternal representations to guide behavior  from Pfizer and Novartis. He also received consultation and/or speaker fees from Pfizer, Eli Lilly, AstraZeneca, Shire, Novartis, and Lundbeck. The other authors have no conflicts of interest to disclose.


Neuropsychological group study methodology is considered one of the primary methods to further understanding of the organisation of frontal ‘executive’ functions. Typically, patients with frontal lesions caused by stroke or tumours have been grouped together to obtain sufficient power. However, it has been debated whether it is methodologically appropriate to group together patients with neurological lesions of different aetiologies. Despite this debate, very few studies have directly compared the performance of patients with different neurological aetiologies on neuropsychological measures. The few that did included patients with both anterior and posterior lesions.We present the first comprehensive retrospective comparison of the impact of lesions of different aetiologies on neuropsychological performance in a large number of patients whose lesion solely affects the frontal cortex. We investigated patients who had a cerebrovascular accident (CVA), high (HGT) or low grade (LGT) tumour, or meningioma, all at the post-operative stage. The same frontal ‘executive’  and nominal (Graded Naming Test) tasks were compared. Patients' performance was compared across aetiologies controlling for age and NART IQ scores. Assessments of focal frontal lesion location, lesion volume, global brain atrophy and non-specific white matter (WM) changes were undertaken and compared across the four aetiology.We found no significant difference in performance between the four aetiology subgroups on the ‘frontal’ executive and nominal tasks. However, we found strong effects of premorbid IQ on all cognitive tasks and robust effects of age only on the frontal tasks. We also compared specific aetiology subgroups directly, as previously reported in the literature. Overall we found no significant differences in the performance of CVA and tumour patients, or LGT and HGT patients or LGT, HGT and meningioma's on our four frontal tests. No difference was found with respect to the location of frontal lesions, lesion volume, global brain atrophy and non-specific WM changes between the subgroups.Our results suggest that the grouping of frontal patients caused by different aetiologies is a pragmatic, justified methodological approach that can help to further understanding of the organisation of frontal executive functions. •Impact of different aetiology on frontal patient's performance.•No difference between aetiology subgroups in frontal lesion characteristics.•No difference between aetiology subgroups in neuropsychological performance.•The importance of accounting for age, NART IQ and lesion characteristics.•Grouping frontal patients by different aetiologies is methodologically appropriate. Neuropsychological group study methodology is considered one of the primary methods to further understanding of the neuroanatomical architecture underlying cognitive functions. However, to obtain sufficient power with this methodology it is necessary to recruit rather large numbers of neurological patients. If too few patients are used, the results are inevitably inconclusive. Thus, to investigate neuro-cognitive architectures, patients with different aetiologies such as vascular (CVA) or tumour (different types of brain tumours) are often combined. A typical example of this approach is given by research investigating the organisation of frontal ‘executive’ functions. Different aspects of executive functioning have been explored in influential studies grouping patients with frontal lesions caused by stroke or tumours. Thus, However, it is well known that stroke and tumours affect brain structures in several different ways. For example, CVAs such as ischaemic stroke causes cell death within the affected area. In contrast, neural activity can persist in areas infiltrated by low grade tumours e.g. . The onsIn the literature it has been debated if, for the purpose of neuropsychological investigation, the grouping together of patients with different neurological aetiologies is methodologically appropriate e.g.  argued tn=19; 10 left, 9 right) and tumour  patients. Using mainly CT scans, the investigators attempted to match anatomically the patients for lesion size and location on a case-by-case basis. The authors reported that the left stroke patients performed significantly worse than the left tumour patients on 4/6 subtests from the Multilingual Aphasia Examination battery. For right hemisphere patients, differences were less clear cut  and with low-grade tumours  on the WAIS-III and Halstead–Reitan battery. High grade performed worse than low grade tumour patients on the WAIS-III and almost all the subtests of the Halstead–Reitan battery. Similarly, n=31) performed significantly poorer than low grade tumour patients (n=37) on two out of ten neuropsychological measures . n=25), low grade tumour patients (n=28) and meningioma patients (n=15). The authors reported that in two of the four tests, high grade tumour patients performed significantly worse than low grade tumour patients post-operatively. However, there was a significant post-operative decline in three tests in the low grade tumour group.Other studies have investigated whether patients with high and low grade tumours differ in terms of neuropsychological test performance . Unfortun=106) and less malignant gliomas , with all patients at the post-operative stage. No effect of tumour malignancy was found, although significant effects for tumour lateralisation and type of therapy  were reported. Talacchi et al. .In contrast, other studies have reported no significant differences between high and low grade tumour patients on extensive batteries of tests. i et al.  also docIt should be noted that none of the studies reviewed above attempted a comprehensive comparison between aetiologies, such as vascular and different type and grades of tumours. It is often unclear whether studies reporting on tumour patients were tested at the pre-operative or post-operative stage. All previous studies have included patients with both anterior and posterior lesions. Moreover, most did not characterize lesion location at a finer level than the damaged hemisphere, the only exception being the study by The aim of our retrospective study was to carry out the first comprehensive comparison of the impact of different aetiologies on neuropsychological performance. We reviewed a large number of patients with CVA; high and low grade tumours as well as meningiomas, all at the post-operative stage. The lesions of all patients were unilateral and confined to the frontal lobes. We determined the location of the frontal lesions and for a subsample of patients the total lesion volume. Measures of global atrophy and white matter (WM) changes were also undertaken. We compared the performance of the frontal patients on the same frontal ‘executive’ and nominal tasks across the aetiologies whilst taking into account differences in age and premorbid levels of functioning. Apriori comparisons of specific aetiologies groups were also conducted. Using these we sought to investigate further the findings of previous studies .22.1One hundred and sixty four patients with a unilateral lesion confined to the frontal lobes resulting from a cerebrovascular accident (CVA) or a brain tumour, attending the Neuropsychology Department at the National Hospital for Neurology and Neurosurgery, Queen Square, London, were retrospectively screened for study eligibility. Our exclusion criteria were (i) age>80 years, (ii) current or previous psychiatric disorders, (iii) current or previous neurological disorders including previous CVAs or tumours, (iv) presence of metastatic tumours, (v) previous chemotherapy, (vi) visual or motor impairment, (vii) previous head trauma, (viii) history of excessive alcohol or drug use, (ix) no MRI or CT scan results available, (x) no neuropsychological assessment available, (xi) a score below the 5th percentile on a test of general intelligence , (xii) gross perceptual or language impairment. Non-native English speakers were only included in the study if they obtained a score at or above the 25th percentile on the National Adult Reading Test NART, .n=29), the low grade tumour group , the high grade tumour group  and the meningioma group (n=27).Application of the exclusion criteria resulted in 100 patients being retrospectively included in the study. For all patients the diagnosis was confirmed by neurological investigation. Tumour grade was confirmed by histopathological studies following resection or biopsy. All tumour patients had undergone tumour resection prior to neuropsychological assessment. Patients were assigned to four groups based on lesion aetiology; the CVA group . Fifty three patients with frontal lesions included in this study have had aspects of their profiles reported previously .2.2n=76; n=5 hard copies) or CT scan (n=19) were available for analysis. Digital brain MRI scans were obtained on systems operated at .5 (n=1) or 1.5 (n=54) or 3 (n=16) Tesla and included the acquisition of an axial dual-echo and an axial and coronal T1-weighted scan. CT scans were obtained using spiral CT systems. Axial images were collected with an effective slice thickness of 5 mm and pitch of 1.5. Only T1-weighted MRI scans (or CT scans when MRI was not available) were used for the assessment of frontal lesions. We conducted an analysis of the total frontal lesion volumes only for a subset of patients. These were the patients for whom we obtained the largest number of MRI scans at the same magnetic strength (1.5 T). DE and FLAIR images were used for the assessment of global brain atrophy and non-specific WM changes.Both MRI and CT data were used, as our principal goal was to recruit a large number of patients. Hard copies or digital records of all scans were reviewed by two independent neurologists (MB and BS) who were blind to the medical history of each patient. For 95 out of 100 patients MRI . The total lesion volume was then calculated for every patient.2.2.3Visual quantification of global brain atrophy was assessed using FLAIR or CT scans, according to the method proposed by 2.2.4To visually quantify WM changes we used the Fazekas' rating scale , which i2.31.Raven's Advanced Progressive Matrices RAPM; , an unti2.Stroop Test , a test 3.Letter fluency ‘S’ Test FAS; , a test 4.Trail Making Test, Part B , a test 5.The Graded Naming Test GNT; , a test The neuropsychological battery comprised a series of widely used clinical tests with published standardised normative data collected from large control samples. The National Adult Reading Test (NART) was given to estimate optimal pre-morbid levels of functioning . The res2.4http://www-01.ibm.com/software/analytics/spss/).All statistics were carried out using SPSS Statistics  or an analysis of variance (ANOVA) . This was used to test for significant difference between the four aetiologies .2.4.210 transformation. To account for the two sub-scales used in the WM analysis, Kruskal–Wallis non-parametric ANOVA was corrected using a Bonferroni adjustment (p<.025). Brain atrophy and WM changes are known to be associated with aging , one-way ANOVA  and Kruskal–Wallis non-parametric ANOVAs  were used in the neuroimaging analysis to test for significant differences between the aetiology subgroups. There was a significant difference in variance between aetiology subgroups in frontal lesion volumes. This was corrected with a loging e.g. . To exam2.4.310 transformation. All neuropsychological data was analysed using ANCOVAs, with age and NART as covariates. Partial eta squared was used to estimate the effects size for age, NART IQ and aetiology. To investigate the effect of lateralisation, patients were classified according to hemisphere damage  and their neuropsychological performance was examined. To investigate the effect of aetiology, patients were classified according to their aetiology subgroups  and their neuropsychological performance was examined.The neuropsychological findings were analysed to ascertain if they were normally distributed and to identify outliers. The findings were also assessed for homogeneity of variance. Negative skew was found for the GNT and the Stroop Test. This was corrected using square root transformation . A positive skew was found for Trail Making Part B. This was corrected with a logTo examine the impact of the covariates on performance, linear regression analysis was conducted on each of the frontal tasks using age and NART as predictor variables. Additionally three planned comparisons of specific aetiology subgroups, motivated by previous studies, were carried out. Individual ANCOVAs were used to compare the neuropsychological performance of (i) CVA and one group including all tumour patients =10.581, p<.001). Post hoc analysis revealed that the Meningioma group were significantly older than all other aetiology subgroups  and there was a trend for LGT to be somewhat younger then CVA (p=.09). There was no significant main effect of NART IQ =1.882, p>.138).Demographic results for the four aetiology subgroups  are shown in 3.2χ2=5.929, p=.115), left lateral =1.569, p=.666), right lateral: =1.308, p=.727) and orbital frontal areas: =1.097, p=.778; see T1-w MRI or CT scans were available for 94 out of the 95 patients. We compared the four aetiology subgroups on the number of patients with focal brain damage in the four frontal areas. There was no difference across the aetiology subgroups in the numbers of patients with damage to medial =1.384, p=.259.Volumetric analysis was available for 52 out of 95 patients . We found no significant difference in the total frontal lesion volume between the four aetiology subgroups 3.4χ2=4.633, p=.201). This suggests that the amount of brain atrophy did not differ between patients from different aetiology subgroups. A linear regression analysis indicated that there was a significant effect of age on the increment scores on the brain atrophy rating scale =32.13, p<.001).FLAIR or CT scans were available for 80 out of the 95 patients. These were analysed using 3.5χ2 =13.843, p=.003; DWMH: χ2 =12.392, p=.006). Post-hoc pair-wise comparisons using Mann–Whitney non parametric analysis indicated that these differences were due to meningioma patients having more severe white matter changes than the others patient subgroups .DE, FLAIR or CT scans were available for 80 out of the 95 patients. These were analysed using the Fazekas' rating scale for the quantification of WM changes. R2=.17, F=16.37, p<.001; DWMH: R2=.17, F=16.09, p<.001). As stated above, the patients in the meningioma group were significantly older than the other three groups. To test if the severity of WM changes can be attributed to differences in age we calculated a decrement score for each patient. A decrement score was defined as the patients’ observed white matter score on each Fazekas scales minus their predicted white matter scores based on the results of the linear regression analyses. The decrement scores were then used to compare the white matter changes between the four aetiologies subgroups using Kruskal–Wallis non parametric ANOVA. After accounting for age, no significant difference was found between the four aetiologies in both periventricular hyper/hypo intensity (PVH) and deep white matter hyper/hypo intensity signal (DWMH) sub-scales =4.267, p=.234; DWMH: χ2 =2.580, p=.461). This indicated that differences between the aetiology subgroups in the severity of WM changes can be attributed to differences in the ages of the aetiology subgroups.Linear regression analyses indicated that there was a significant effect of age on the increment scores on both Fazekas subscales =14.018, p<.001, pη2=.175 and F=10.203, p=.002, pη2=.134, respectively), Stroop Test =57.464, p<.001, pη2=.520 and F=7.473, p=.008, pη2=.124, respectively) and Letter Fluency ‘S’ Test =14.630, p<.001, pη2=.151 and F=12.674, p=.001, pη2=.134, respectively). There was a significant effect of age on Trail Making Test Part B =34.298, p<.001, pη2=.372). There was a significant effect of NART IQ on GNT score =83.484, p<.001, pη2=.490).We compared the performance of left and right frontal patients on the neuropsychological tests. Age and NART IQ significantly affected performance on RAPM =.043, p=.837, pη2=.001), Letter Fluency ‘S’ Test =1.328, p=.252, pη2=.016), Trail Making Test Part B =1.84, p=.18, pη2=.031) and the GNT =.734, p=.394, pη2=.008). However, a significant group effect was found on the Stroop Test =13.348, p=.001, pη2=.201), reflecting worse performance of the left frontal patients than right frontal patients  for the RAPM  on the five neuropsychological tests .RAPM. There were significant effects of age and NART IQ on patients' performance on the RAPM =13.328, p=.001, pη2=.172 and F=14.177, p<.001, pη2=.181, respectively). However, there was no main effect of group, with no significant difference in the neuropsychological performance of the four aetiology subgroups =1.578, p=.203, pη2=.069, see Stroop Test. Age and NART IQ significantly affected performance =31.623, p<.001, pη2=.383 and F=6.541, p=.014, pη2=.114, respectively). Again we found no main effect of group, with no significant difference in performance between the four aetiology subgroups =.199, p=.896, pη2=.012, see Letter Fluency ‘S’ Test. Age and NART IQ significantly affected performance =8.078, p=.006, pη2=.092 and F=11.378, p=.001, pη2=.125, respectively). Again there was no main effect of group, with no significant difference in performance between the four aetiology subgroups =.319, p=.812, pη2=.012, see Trail Making Test Part B. Age significantly affected performance =21.767, p<.001, pη2=.280). NART IQ trended towards significantly affecting performance =3.506, p=.066, pη2=.059). There was no significant difference in performance on this task between the four aetiologies after accounting for age and NART IQ scores =1.796, p=.158, pη2=.088, see Graded Naming Test. Only NART IQ was found to significantly affect performance =82.171, p<.001, pη2=.492). There was no main effect of group, with no significant difference in performance between the four aetiology subgroups =2.02, p=.117, pη2=.067).3.7.1F=.390, p=.761, pη2=.039; Stroop Colour-Word test: F=.855, p=.477, pη2=.09; Letter Fluency ‘S’: F=.447, p=.721, pη2=.034; Trails Making test Part B: F=2.226, p=.107, pη2=.193; GNT: F=.526, p=.667, pη2=.037).We also compared the cognitive performance of the subsample of 52 patients for whom we conducted a volumetric lesion analysis. Similarly to the results reported above, we found no significant difference across the four different aetiology groups on the five neuropsychological tests =14.366, p<.001, pη2=.183 and F=9.007, p=.004, pη2=.123, respectively) Stroop Colour-Word Test =56.404, p<.001, pη2=.525 and F=7.825, p=.007, pη2=.133, respectively), Letter Fluency ‘S’ Test =13.907, p<.001, pη2=.148 and F=12.245, p=.001, pη2=.133, respectively). There was a significant effect of age on performance on Trail Making Test Part B =35.586, p<.001, pη2=.389). On the GNT, there was a significant effect of NART IQ on performance =81.975, p<.001, pη2=.491).In accordance with F=.138, p=.711, pη2=.002); Stroop Colour-Word Test =.450, p=.506, pη2=.009); and Letter Fluency ‘S’ Test =.226, p=.636, pη2=.003). We found a significant difference in the performance of CVA and tumour patients on the Trail Making Test Part B =4.890, p=.031, pη2=.08) and a non-significant trend on the GNT =3.202, p=.077, pη2=.036). Given these two latter results we conducted post-hoc analyses for the Trail Making Part B and GNT tests comparing the performance of the CVA patients with each tumour subgroup. We found no significant difference in Trail Making part B and GNT tests' performance between CVA and LGT =2.443, p=.128, pη2=.073; GNT =2.808, p=.101, pη2=.061). Similarly we found no significant difference between CVA and meningioma’s in performance on the Trail making test B and on the GNT =2.203, p=.149, pη2=.071 and F=.369, p=.547, pη2=.008). However we found a significant difference between CVA and HGT in performance on the GNT =5.335, p=.026, pη2=.118) and a non-significant trend on the Trail Making Test Part B =3.223, p=.083, pη2=.097; suggesting that the CVA patients performed worse than HGT on these two tests.We found no main effect of group, with no significant difference in performance between CVA and tumour aetiology subgroups on the RAPM =.230, p=.633, pη2=.004), Letter Fluency ‘S’ Test =.731, p=.395, pη2=.009), Trail Making Test Part B =.804, p=.374, pη2=.014), the GNT =.200, p=.656, pη2=.002). The only exception was the Stroop Colour-Word Test =13.654, p=.001, pη2=.211) where left frontal patients performed worse than right frontal patients.We found no main effect of laterality, with no difference in the performance of left and right frontal patients on the RAPM =.449, p=.505, pη2=.007; Stroop Colour-Word Test: F=.741, p=.393, pη2=.014; Letter Fluency ‘S’ Test: F=.048, p=.826, pη2=.001; Trail Making Test Part B: F=1.477, p=.229, pη2=.026; and GNT: F=.129, p=.720, pη2=.002).We found no significant interactions between aetiology and laterality on any neuropsychological tasks =5.95, p=.022, pη2=.199), Stroop Colour-Word Test =4.839, p=.038, pη2=.174), Letter Fluency ‘S’ Test =8.526, p=.006, pη2=.191), Trail Making Test Part B =10.06, p=.004, pη2=.287) and GNT =24.867, p<.001, pη2=.402). For all neuropsychological tests, there was no main effect of group, with no significant difference in performance between LGT and HGT aetiology subgroups: Stroop Colour-Word Test =.480, p=.495, pη2=.02), Letter Fluency ‘S’ Test =.38, p=.542, pη2=.01), Trail Making Test Part B =.246, p=.624, pη2=.01), GNT =.516, p=.477, pη2=.014). However there was a trend towards significance for the RAPM =3.318, p=.081, pη2=.121).The performance of the LGT and HGT patients was compared . There w3.9.3F=6.204, p=.017, pη2=.121 and F=12.945, p=.001, pη2=.223, respectively), the Stroop Colour-Word Test =9.378, p=.004, pη2=.216 and F=8.849, p=.005, pη2=.207, respectively), Letter Fluency ‘S’ Test =5.778, p=.019, pη2=.092 and F=10.682, p=.002, pη2=.158, respectively) and Trail Making Test Part B =7.510, p=.009, pη2=.169 and F=5.716, p=.022, pη2=.134, respectively). On the GNT, there was only a significant effects of NART IQ on performance =58.917, p<.001, pη2=.491). For all neuropsychological tests, there was no main effect of group, with no significant difference in performance between the three aetiology subgroups on the RAPM =2.224, p=.120, pη2=.09), Stroop Colour-Word Test =.182, p=.835, pη2=.011), Letter Fluency ‘S’ Test =.168, p=.845, pη2=.006), Trail Making Test Part B =.142, p=.868, pη2=.008) and GNT =.849, p=.433, pη2=.027).The performance of the LGT, HGT and Meningioma patients was compared. There was a significant effect of age and NART IQ on performance on the RAPM  did not differ in handedness, gender, education or premorbid intelligence. There was a significant effect of age, with LGT patients being somewhat younger and meningioma patients significantly older. This is in keeping with the literature reporting that LGT generally affects younger adults , medial and orbitofrontal regions. Similarly, no significant difference across the four aetiologies was found in the total frontal lesion volumes or the amount of global brain atrophy. We did find significantly more white matter changes in the meningioma group. However, when we compared white matter changes, after accounting for age, no significant difference between the aetiology subgroups was found. This suggests that the reported difference in white matter changes is most likely due to age-related changes. Indeed it is known that age is associated with an increase in white matter changes e.g. .α=.05 and on the effect size obtained in the current study, 902 patients would have been needed to achieve a significant effect of aetiology on the Stroop task  and on a nominal test (GNT). A previous study on a rather small sample of patients with frontal lobe epilepsy similarly reported no effect of aetiology on frontal tasks . Of courInterestingly, while not finding an effect of aetiology on cognitive performance, we did document a significant effect of premorbid IQ on all cognitive tasks and a significant effect of age on the four frontal executive tests. In keeping with our current findings, a decline in performance on frontal ‘executive’ tasks has been reported in healthy aging and in patients with head injury . This suWe conducted three more focused analyses comparing specific aetiology subgroups directly. These comparisons have been previously carried out by others, although no previous studies compared all four aetiologies, with all tumours at the post-operative stage. We first compared CVA and tumours. Again, no significant difference between aetiologies was found in performance on all but one of the neuropsychological test. The only exception was found on Trail-Making Test part B; however, this result would not survive Bonferroni correction since there is no a priori reason to assume that aetiology should affect only this particular executive test. The lack of difference in performance across CVA and tumours is in contrast with the only study which directly compared these two aetiologies . NotablySecondly, we compared the neuropsychological performance of the LGT and HGT groups. We found no significant difference in cognitive performance between the tumour types. The only exception was a non-significant trend with LGT tending to perform worse on the RAPM. Two previous studies also reported no significant difference in performance between LGT and HGT patients, at the post-operative stage of treatment . In otheIn the literature it has been debated whether the grouping of patients with different neurological aetiologies is methodologically appropriate for the purpose of neuropsychological investigation. When investigating neuro-cognitive architecture it is critical to have sizeable groups of patients so sufficient power can be obtained to search for significant effects. Our main result indicated that after accounting for the significant effects of age and premorbid IQ on cognitive performance there were no significant differences between frontal patients of different aetiologies. This result suggests that the grouping together of patients with different aetiologies but similar site and size of lesions is a pragmatic procedure that helps to make this possible. In our view any averaging procedure of neuropsychological patients is liable to suffer from potential artefacts, but to eliminate all possible artefacts makes it impossible in practise to obtain useful results. One must balance the danger of artefacts with the utility of increased sample size. Our study has established that combining across vascular and different types of tumour pathologies is not likely to produce a major distortion in the pattern of neuropsychological performance, at least for frontal patients. Our results therefore suggest that grouping patients with focal frontal lesions caused by different aetiologies is a pragmatically justified methodological approach that can help to further the understanding of the organisation of frontal executive functions.


Malus domestica Borkh.) is a commercially important fruit worldwide. Detailed information on genomic DNA polymorphisms, which are important for understanding phenotypic traits, is lacking for the apple. We re-sequenced two elite apple varieties, ‘Nagafu No. 2’ and ‘Qinguan,’ which have different characteristics. We identified many genomic variations, including 2,771,129 single nucleotide polymorphisms (SNPs), 82,663 structural variations (SVs), and 1,572,803 insertion/deletions (INDELs) in ‘Nagafu No. 2’ and 2,262,888 SNPs, 63,764 SVs, and 1,294,060 INDELs in ‘Qinguan.’ The ‘SNP,’ ‘INDEL,’ and ‘SV’ distributions were non-random, with variation-rich or -poor regions throughout the genomes. In ‘Nagafu No. 2’ and ‘Qinguan’ there were 171,520 and 147,090 non-synonymous SNPs spanning 23,111 and 21,400 genes, respectively; 3,963 and 3,196 SVs in 3,431 and 2,815 genes, respectively; and 1,834 and 1,451 INDELs in 1,681 and 1,345 genes, respectively. Genetic linkage maps of 190 flowering genes associated with multiple flowering pathways in ‘Nagafu No. 2,’ ‘Qinguan,’ and ‘Golden Delicious,’ identified complex regulatory mechanisms involved in floral induction, flower bud formation, and flowering characteristics, which might reflect the genetic variation of the flowering genes. Expression profiling of key flowering genes in buds and leaves suggested that the photoperiod and autonomous flowering pathways are major contributors to the different floral-associated traits between ‘Nagafu No. 2’ and ‘Qinguan.’ The genome variation data provided a foundation for the further exploration of apple diversity and gene–phenotype relationships, and for future research on molecular breeding to improve apple and related species.Apple ( Malus domestica Borkh.) is one of the most commercially important fruit worldwide, with over 60 million tons produced each year . There are more than 10,000 documented cultivars of apples  technologies have enabled the identification of genome-wide patterns of genetic variation in perennial fruit crops in a rapid, efficient, relatively low cost, and high-throughput manner . Geneticentified . Structuentified . Multiplentified .MdFT1 and/or MdFT2 might also be associated with flowering and fruiting by interacting with proteins of the TCP and VOZ families of transcription factors in apple  have been established in model annual plants . In perein apple . To dateTM 2000 to re-sequence the genomes of ‘Nagafu No. 2’ and ‘Qinguan,’ and to analyze their genetic structures. We developed effective DNA markers to explore agronomic traits-related genes by comparing the ‘Nagafu No. 2’ and ‘Qinguan’ sequences with the published reference genome. A comparison of the variation data defined potential genomic regions and metabolic pathways related to floral-associated traits. The genomic resources provided here are useful for comparative genomics and molecular breeding in apple and related species.We used Solexa sequencing technology and the Illumina HiSeqMalus domestica Borkh.) ‘Nagafu No. 2’ and ‘Qinguan’ were used as materials for re-sequencing. Physiological differentiation stage of apple flower bud was from May 5th, 2014  to June 25th, 2014 . And bud growth including length, width, and fresh weight during the flower bud physiological stage  can be seen in our published paper  in the Shaanxi Province of China . Young leaves of apple varieties , reads with adaptor sequences, and duplicated reads were eliminated. The remaining high-quality data were used for mapping.Genomic DNA was extracted from young leaves of ‘Nagafu No. 2’ and ‘Qinguan’ using a modified CTAB method . The DNA3 under default parameters, with a small modification: allowing no more than three mismatches in the sequence and not allowing gaps (-o 0). Reads that aligned to more than one position of the reference genome were filtered and used to determine reads mapping to multiple positions in the reference and unmapped reads. After mapping, the reads were sorted by their scaffold coordinates. The mapping result was used to detect DNA polymorphisms, such as SNPs, INDELs, and SVs.We used the published genome of ‘Golden Delicious’ as a reference . We mapp4 was used to detect SNPs using the following parameters: u -fa -C 50 – bcftools view -I -N- b-v -c -g. The detected SNPs were screened using the following criteria: coverage depth ≥2×, heterozygous locus ≥3×, average depth ≤3×, no less than 20 for the quality value of the genomic type, and discarding SNPs detected in repeat regions.SAMtools software5 and Breakdancer6 software, with their default parameters. To obtain reliable SVs, the detected SVs were returned to the pair-end reads alignments between samples and the reference, and were validated under the following criteria: 2× to 100× for coverage depth and more than 20 for SV quality. We detected insertion (INS), deletion (DEL), deletion including insertion (IDE), inversion (INV), intra-chromosomal translocation (ITX), and inter-chromosomal translocation (CTX) SVs. INDELs were defined as the insertion or deletion of 1–5 bp.Structural variations (SVs) were detected using Pindel7. Polymorphisms in the gene region and other genome regions were annotated as genic and intergenic, respectively. The genic SNPs and SVs were classified as exonic and intronic based on their location. SNPs in coding DNA sequences (CDSs) were further separated into synonymous and non-synonymous using Genewise8.The locations of SNPs, INDELs, and SVs were based on the annotation of gene models from the reference genome database9 analysis of genes with DNA polymorphisms identified those enriched in particular pathways, based on the hypergeometric distribution test  with related genes.Using the ‘Golden Delicious’ gene set as the reference, genes containing DNA polymorphism were identified in the ‘Nagafu No. 2’ and ‘Qinguan’ apple varieties. The genes associated with the DNA polymorphisms were annotated in databases, such as Swissprot, COG, Nr, and GO, for both ‘Nagafu No. 2’ and ‘Qinguan’ apples . In addiion test . The FisFT promoter region were based on those described in a previous study on apples . The fragment was then ligated into the plasmid pMD18-T vector, transformed into Escherichia coli DH5α competent cells , and sequenced . In addition, we predicted the transcription factor binding sites in the FT promoters of the two apple varieties using Plant CARE10.The primers used to amplify the n apples . Using tTM First-Strand cDNA Synthesis Kit . The cDNA was diluted 10-fold, and 2 μL was used as the template for qRT-PCR analyses. Each qRT-PCR reaction mixture contained 10.0 μL SYBR Premix Ex TaqTM , 0.4 μL each primer (10 μM), 2 μL cDNA, and 7.2 μL RNase-free water in a total volume of 20 μL. The reactions were incubated in an iCycler iQ5 (BIO-RAD) for 30 s at 95°C; followed by 40 cycles of 5 s at 95°C and 35 s at 60°C. Then, an additional 81 cycles were run for the melt curve. The qRT-PCR primers were designed using primer 3 software11. The primers used in the qRT-PCR experiments are listed in Supplementary Table S1. Each reaction was performed with three replicates.Total RNA was isolated from each sample using a modified CTAB method . The conThe expression levels of the flowering genes in the buds and leaves of ‘Nagafu No. 2’ and ‘Qinguan’ apple varieties were analyzed by one-way analyses of variance with Tukey–Kramer multiple comparison tests using DPS software, version 7.0 .Table 1). ‘Qinguan’ is a hybrid progeny of ‘Golden Delicious’ and ‘Cockscomb’ that shows high drought resistance during the whole growth period. ‘Qinguan’ flowers easily (The flowering rate in 6-year-old trees is ∼70%), has a high yield and is easy to manage (Table 1). These apple varieties differ in a number of floral-associated traits (Table 1). The two easy-flowering varieties (‘Qinguan’ and ‘Golden Delicious’) had higher proportions of spurs, budding rates, flower formation rates, and formed spurs and full blooms at earlier dates compared with ‘Nagafu No. 2’ (Table 1). The variation in the biological traits of these three varieties provides the basis to study gene-trait associations by examining the sequence polymorphisms and structural variations at the whole-genome level.‘Nagafu No. 2’ is a hybrid progeny of ‘Red Delicious’ and ‘Ralls Genet’ introduced to China in 1966. It has the good agronomic traits of fleshy fruit, delicate flavor, and great storability; however, it has difficulty flowering (The flowering rate in 6-year-old trees is just ∼20%), poor disease resistance, and environmental adaptation (Table 2). For the clean reads, 80.22% from ‘Nagafu No. 2’ and 81.52% from ‘Qinguan’ were mapped successfully onto the reference genome of ‘Golden Delicious’ (Table 2). Details of the data quality, including base distribution, cycle average phred score, and quality distribution, of the two apple varieties are presented in Supplementary Figures S1 and S2, respectively. The sequencing depth distribution and the distribution on chromosomes are shown in Supplementary Figures S3 and S4, respectively. Compared with the reference genome, the identities of ‘Nagafu No. 2’ and ‘Qinguan’ were 98.62% and 98.7%, respectively (Table 2). The re-sequencing data have been deposited in NCBI Sequence Read Archive (SRA12). And accession number was SRP072330.Whole-genome sequencing produced 171,118,509 reads , 82,663 SVs , and 1,572,803 INDELs were detected in ‘Nagafu No. 2,’ while 2,262,888 genome-wide SNPs, 63,764 SVs and 1,294,060 INDELs were detected in ‘Qinguan’ (Supplementary Table S2). The average densities of detected SNPs, SVs, and INDELs for ‘Nagafu No. 2’ and ‘Qinguan,’ when compared to samples the reference genome, were 4,546.9 and 3,746.0 SNPs per Mb, respectively, 135.9 and 105.3 SVs per Mb, respectively, and 2,584.1 and 2,145.4 INDELs per Mb, respectively (Supplementary Table S2).Based on the alignment results between samples and the reference genome, 2,771,129 genome-wide SNPs . Among the variations detected between the samples and reference genome ‘Golden Delicious,’ the highest numbers of SNPs, 231,577 in ‘Nagafu No. 2,’ and 193,484 in ‘Qinguan,’ were observed on chromosome 15, while the lowest numbers of SNPs, 104,010 in ‘Nagafu No. 2’ and 99,017 in ‘Qinguan,’ were observed on chromosome 16 (Supplementary Table S2). The highest numbers of SVs were observed on chromosome 15, 6,817 in ‘Nagafu No. 2’ and 5,475 in ‘Qinguan,’ while the lowest numbers of SVs, 3,448 in ‘Nagafu No. 2’ and 2,786 in ‘Qinguan’ were observed on chromosome 16 (Supplementary Table S2). The highest numbers of INDELs, 131,976 in ‘Nagafu No. 2’ and 109,667 in ‘Qinguan,’ were observed on chromosome 15, and the lowest numbers of INDELs, 60,055 in ‘Nagafu No. 2’ and 56,509 in ‘Qinguan,’ were observed on chromosome 16 (Supplementary Table S2).Detailed distribution information for the SNPs, SVs, and INDELs in both ‘Nagafu No. 2’ and ‘Qinguan’ samples identified the landscape of genetic variation in the two apple varieties . The three peripheral circles represent the distribution of polymorphisms in ‘Nagafu No. 2,’ ‘Qinguan,’ and ‘Golden Delicious,’ respectively . These circles indicate the statistical information for total SNPs (blue line), non-synonymous SNPs (red line), and SNPs in structural domains (green line) on each chromosome. The promoter circles indicate the SNP numbers of ‘Nagafu No. 2’ (blue line), ‘Qinguan’ (red line), and Golden Delicious (green line), which are located in the 200 bp upstream of each coding region . Inside the promoter circles, there are three grouped circles, which represent the distribution of flowering genes on each chromosome of ‘Nagafu No. 2,’ ‘Qinguan,’ and ‘Golden Delicious.’ We chose flowering genes mainly based on previous research in the model plant Arabidopsis thaliana . The inner circles represent the SV distribution on each chromosome of ‘Nagafu No. 2’ (blue line) and ‘Qinguan’ (red line).Our result showed that the distribution of polymorphisms was uneven within chromosomes , and all of the chromosomes in both varieties were comprised of a mixture of SNP-dense and -sparse regions . The number of SNPs  and SVs  in ‘Nagafu No. 2’ were significantly higher than in ‘Qinguan’  for chromosome 1. Other chromosomes showed similar results . Additionally, the distribution patterns of the two polymorphism types were similar in the two varieties .In addition, detailed information on the distribution of SNPs and SVs detected between ‘Nagafu No. 2’ and ‘Qinguan’ on the 17 chromosomes is shown in Supplementary Table S3). The proportions of transitions and transversions on individual chromosomes were very similar, but the proportions of transitions were significantly higher than the proportions of transversions in both samples (Supplementary Table S3). The proportions of heterozygosity were significantly higher than the proportions of homozygosity in the two samples, and the proportion of heterozygosity in ‘Qinguan’ was significantly higher than the proportion of heterozygosity in ‘Nagafu No. 2’ (Supplementary Table S3). The highest proportions of SNP heterozygosity, 89.66 and 93.67%, were observed on chromosome 7 of ‘Nagafu No. 2’ and ‘Qinguan,’ respectively, while the lowest proportions of SNP heterozygosity, 4.09 and 86.08%, were observed on chromosome 2 of ‘Nagafu No. 2’ and chromosome 8 of ‘Qinguan,’ respectively (Supplementary Table S3).The SNPs detected when comparing the two samples with the reference genome were classified as transitions (C/T and G/A) or transversions  based on nucleotide substitutions (Supplementary Table S4). In ‘Nagafu No. 2’ and ‘Qinguan,’ 63,764 and 82,663 SVs, respectively, were detected (Supplementary Table S2). There was no significant difference in the percentage of each SV between ‘Nagafu No. 2’ and ‘Qinguan.’ Among them, DEL and INS were the major SVs, with 46,878 (56.71%) and 31,800 (38.47%), respectively, for ‘Nagafu No. 2,’ and 36,428 (57.13%) and 24,001 (37.64%), respectively, for ‘Qinguan’ . INX  and INV  were the minor SVs in the two varieties . Among the variations detected between samples and ‘Golden Delicious,’ the highest densities of SVs were 162.97 per Mb, observed on chromosome 11 of ‘Nagafu No. 2’ and 114.42 per Mb on chromosome 17 of ‘Qinguan.’ The lowest densities of SVs were 111.31 per Mb and 89.94 per Mb observed on chromosome 1 in ‘Nagafu No. 2’ and ‘Qinguan,’ respectively (Supplementary Table S4).In addition, six types of SVs, INS, DEL, IDE, INV, ITX, and CTX, were identified in both cultivars, based on the annotation of ‘Golden Delicious’ genome . In the CDS regions of ‘Nagafu No. 2’ and ‘Qinguan,’ 509 and 414 INS, respectively, and 841 and 678 DEL, respectively, were identified from the 1-bp INDELs . Detailed distribution information on INDELS of other sizes is shown in Figure 3. We identified 171,520 non-synonymous SNPs in 23,111 genes for ‘Nagafu No. 2’ and 147,090 non-synonymous SNPs in 21,400 genes for ‘Qinguan’ apple varieties, but there were relatively small numbers of frameshift INDELs within the genes of both apple varieties (Supplementary Table S5). We also analyzed the distribution of the SNPs in Pfam-containing genes, and the range of the ratio of non-synonymous-to-synonymous SNPs (ns/s SNPs) was 0.48 to 1.4 in these genes, indicating that the Pfam domains may have more amino acid substitutions in the genome .In the genomic regions of ‘Nagafu No. 2’ and ‘Qinguan,’ 4,827 and 3,719 INS, respectively, and 6,331 and 5,091 DEL, respectively, were identified from the 1-bp INDELs . However, the genes with INDELs were mainly involved in sex determination (GO:0007530), succinate metabolic process (GO:0006105), regulation of ion transport (GO:0043269), response to herbivore (GO:0080027), positive regulation of flavonoid biosynthetic process (GO:0009963), and mitochondrial transport , suggesting that the biological functions of genes with different genome variations had significantly different effects on the phenotypes of these apple varieties.The numbers of SNPs, non-synonymous SNPs, SVs, and frameshifts associated with the genes in both ‘Nagafu No. 2’ and ‘Qinguan’ apple varieties can be found in Additional file 2. Additionally, detailed information on the functional and annotation-related information from databases such as Swissprot, Nr, COG, GO, and KEGG for the SNPs, non-synonymous SNPs, SVs, and frameshifts in ‘Nagafu No. 2’ and ‘Qinguan’ apple varieties can be found in Additional file 3. The details of the GO function analysis for genes with SNPs, non-synonymous SNPs, SVs, and INDELs in the two varieties can be seen in Additional files 4, 5, 6, and 7. For example, the GO terms significantly enriched for genes with SNPs and non-synonymous SNPs in both ‘Nagafu No. 2’ and ‘Qinguan’ apple varieties were mainly involved in the defense response (GO:0006952), signal transduction (GO:0007165), arginine catabolic process (GO:0006527), protein targeting to membrane (GO:0006612), and ethylene biosynthetic process (GO:0009693) categories . Genes with non-synonymous SNPs were significantly enriched in 12 pathways, including vitamin B6 metabolism (ko00750), plant hormone signal transduction (ko04075), and oxidative phosphorylation . The genes with INDELs were enriched in 72 KEGG pathways, but only four pathways were significantly enriched: ribosome (ko03010), vitamin B6 metabolism (ko00750), sulfur metabolism (ko00920), and mRNA surveillance pathway .Meanwhile, the KEGG analysis of the genes with DNA polymorphisms also identified particularly enriched pathways . Among them, the different genes with SNPs were enriched in 104 KEGG pathways, and 11 pathways were significantly enriched, including plant hormone signal transduction (ko04075), circadian rhythm (ko04710), photosynthesis (ko00195), and glycerophospholipid metabolism . The distribution of flowering genes was significantly different among the 17 chromosomes within each variety . For example, 18 flowering genes were found on chromosome 10, but there were just three on chromosome 9 . In addition, the locations and distributions of these flowering genes on each chromosome showed large differences among the varieties .We speculated that some of the identified genetic variations might contribute to the phenotypic differences in floral-associated traits; therefore, we focused our analysis on SNPs, SVs, and INDELs associated with flowering genes in genic regions. We used the gene set from the reference ‘Golden delicious’ genome as the control and identified all of the shared variations involved in flowering genes between the difficult-flowering ‘Nagafu No. 2’ and easy-flowering ‘Qinguan’ apple varieties. Genetic linkage maps of ‘Nagafu No. 2,’ ‘Qinguan,’ and ‘Golden Delicious’ were also constructed in association with the 190 flowering genes . In this study, the CO, FT, CRY, and FKF1 genes, which are related to photoperiod, showed higher expression levels in the leaves and buds of ‘Qinguan’ than of ‘Nagafu No. 2’ . The FWA expression level in the buds of ‘Qinguan’ was significantly higher than in ‘Nagafu No. 2’; however, its expression level in the leaves of ‘Qinguan’ was significantly lower than in the leaves of ‘Nagafu No. 2’ . The vernalization pathway-related genes VIN3 and MSI1 were expressed significantly higher in the leaves and buds of ‘Qinguan’ than in those of ‘Nagafu No. 2’ . FLC plays a key role in the autonomous pathway, and its expression in the buds of ‘Qinguan’ was significantly higher than in ‘Nagafu No. 2’; however, in leaves, its expression was significantly higher in ‘Nagafu No. 2’ . In the gibberellin pathway, the expression of GAI in ‘Qinguan’ was significantly higher than in ‘Nagafu No. 2,’ but the downstream gene, AGL24, showed the reverse expression pattern . In addition, a regulatory relationship diagram of these flowering genes in different pathways, as well as models of their expression profiles in leaves and buds between difficult-flowering apple variety ‘Nagafu No. 2’ and easy-flowering apple variety ‘Qinguan,’ are shown in Figure 7.The expression profiles of 15 flowering genes, which were mainly involved in four major flowering promotion pathways, photoperiod, autonomous, vernalization, and gibberellin, were identified in leaves and buds of two apple varieties using RT-PCR .We cloned and amplified the Bioinformatics tools and the rapid development of sequencing technologies have made the complete genome sequencing of many perennial fruit crops possible, providing a starting point to unravel the genetic variation and diversity existing on the genome scale . Genome-Supplementary Table S3). This is unsurprising because ‘Qinguan’ is a hybrid progeny of ‘Golden Delicious’ and ‘Cockscomb.’ A similar phenomenon was reported in rice , and were similar to those in peach (Arabidopsis (Miscanthus sinensis (Table 3). The proportions of genic SVs were also similar between the two varieties (Table 3). The difference in genetic diversity between ‘Nagafu No. 2’ and ‘Qinguan,’ as well as the difference in the distribution of this diversity in different genetic regions, may involve changes in agronomic and floral-associated traits between the two apple varieties.The average proportions of genic SNPs, exons, introns, or intergenic, were similar in the ‘Nagafu No. 2’ and ‘Qinguan’ varieties  showed multiple variation patterns and an uneven distribution of the variation across the genome .In this study, we identified genetic variation, including large numbers of SNPs, SVs, and INDELs, in the two samples when compared with the ‘Golden Delicious’ reference genome. The distributions of these polymorphisms were uneven within the chromosomes. A similar study on peach  in the CDS regions and the whole genome were significantly different between ‘Nagafu No. 2’ and ‘Qinguan,’ and similar results have been seen in other plants . CompareFigure 5), which may explain the differences in flowering-related traits among them. Additionally, genomic variation, such as large-effect SNPs, result in changes to biological characteristics, including growth characteristics, plant phenotypes, and the resistance responses .Previous studies have shown that there are four major flowering pathways photoperiod, autonomous, vernalization, and gibberellin, which are associated with complex gene regulation process . The phoormation . In addi pathway . In the n plants . Gibberen plants  and in mn plants . Indeed,FT promoter region from ‘Nagafu No. 2’ and ‘Qinguan’ to identify and compare the sequence variations between the two varieties. The sequences of the FT promoter regions were 93.1% identical, but 6.9%, including deletions, conversions, and inversions, was completely different , and the expression of the FT gene in buds was significantly higher in ‘Qinguan’ than in ‘Nagafu No. 2’ . In addition, we predicted transcription factor-binding sites, including ARE, G-Box, GATA-motif, and Spl, in FT promoters between the two apple varieties (Supplementary Table S6). This suggested that the observed variation may result in different FT expression patterns between ‘Nagafu No. 2’ and ‘Qinguan’ apple varieties.Sequence variation in promoter regions mediates a transcriptional regulation mechanism associated with anthocyanin biosynthesis genes in grape  and applIn the present study, we identified large-scale genomic variation, including SNPs, INDELS, and SVs, among two elite apple varieties ‘Nagafu No 2,’ ‘Qinguan’ and the reference variety ‘Golden Delicious.’ This can be used as a framework for future comparative and functional genomic analyses in fruit trees, as well as providing information for molecular breeding, allele discovery, and agronomic trait screening in apple. ‘Qinguan’ is an elite variety with strong disease resistance and easy flowering, whereas the fruit quality of ‘Nagafu No. 2’ is better than that of other cultivars. Thus, genome-wide comparison studies of variations involved in floral-related traits and resistance responses will also provide a powerful resource to identify key genes and for function-related research. We also established genetic linkage maps of ‘Nagafu No. 2,’ ‘Qinguan,’ and ‘Golden Delicious’ using 190 flowering genes in multiple flowering pathways and compared the distribution characteristics of the genome variations in these genes, which may contribute to a deeper understanding of the differences among a variety of traits across the genome.Conceived and designed the experiment: HM, XL, ZD, and ZC. Performed the experiments: XL, WK, and LY. Analyzed the data: XL, WK, JM, and NA. Developed the model: LX and KW. Wrote the paper: XL, ZD, and SX. Edited the manuscript: AN.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.