John M Starr

The University of Edinburgh, Edinburgh, Scotland, United Kingdom

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Publications (440)2718.31 Total impact

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    ABSTRACT: sec> Objective To explore the multidimensionality of apathy in ALS, To validate the Dimensional Apathy Scale (DAS) in ALS patients and their carers. Method This was a Scotland- wide questionnaire based study where 83 ALS patients, 75 of their informants and 83 gender-age-education level matched controls were recruited. Control, patient and carer participants completed a standard apathy scale-the Apathy Evaluation scale (AES), the Geriatric Depression Scale-Short form (GDS-15) and the DAS, which is composed of 3 subscales assessing Executive, Emotional and Initiation apathy subtypes. The ALS Functional Rating Scale-Revised (ALSFRS-R) scores were acquired to measure disease related disability. Results ALS patient (self rated) and carer rated comparison on the DAS showed no significant difference on each of the subscales. There was a significant between-subscale dissociation for both the patients and their carers, F(2,296)=160.30, p<.001. ALS patient (self rated) and control responses to the DAS subscales were found to be significantly different, F(2,328)=13.86, p<.001. Further post-hoc t-tests showed that patients (M=12.5, SD=5.1), compared to controls (M=10.2, SD=4.3), were significantly more impaired on the Initiation subscale, t(64)=3.22, p<.01. Additionally, controls were slightly more Emotionally apathetic (M=8.9, SD=3.2) compared to patients (M=7.7, SD=3.3), t(164)=2.28, p<.05. The psychometrics of the DAS were found to be favourable. The Cronbach's standardized alpha values were high, with the carer (0.90) being slightly higher than the patient (0.86). DAS subscales correlated more highly with the AES compared to the GDS-15, again with that of the carers being slightly higher and better discriminating Emotional apathy against depression. The ALSFRS-R was not significantly correlated with any of the DAS subscales. Conclusion Using a multidimensional approach to apathy assessment, our study determined that ALS patients showed an apathy profile, characterised by difficulties in initiation of behaviour and cognition. The DAS was found to be a valid and reliable measurement of the dimensions of apathy, independent of disease related disability. Future research will investigate the relationship of these apathy dimensions and cognitive functioning in ALS and further validate the DAS in other neurodegenerative populations. </sec
    Journal of Neurology Neurosurgery & Psychiatry 09/2015; 86(9). DOI:10.1136/jnnp-2015-311750.33 · 5.58 Impact Factor
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    ABSTRACT: Decline in cognitive ability is a core diagnostic criterion for dementia. Knowing the extent of decline requires a baseline score from which change can be reckoned. In the absence of prior cognitive ability scores, vocabulary-based cognitive tests are used to estimate premorbid cognitive ability. It is important that such tests are short yet informative, to maximize information and practicability. The National Adult Reading Test (NART) is commonly used to estimate premorbid intelligence. People are asked to pronounce 50 words ranging from easy to difficult but whether its words conform to a hierarchy is unknown. Five hundred eighty-seven healthy community-dwelling older people with known age 11 IQ scores completed the NART as part of the Lothian Birth Cohort 1936 study. Mokken analysis was used to explore item responses for unidimensional, ordinal, and hierarchical scales. A strong hierarchical scale ("mini-NART") of 23 of the 50 items was identified. These items are invariantly ordered across all ability levels. The validity of the interpretation of this briefer scale's score as an estimate of premorbid ability was examined using the actual age 11 IQ score. The mini-NART accounted for a similar amount of the variance in age 11 IQ as the full NART (NART = 46.5%, mini-NART = 44.8%). The mini-NART is proposed as a useful short clinical tool to estimate prior cognitive ability. The mini-NART has clinical relevance, comprising highly discriminatory, invariantly ordered items allowing for sensitive measurement, and adaptive testing, reducing test administration time, and patient stress. (PsycINFO Database Record (c) 2015 APA, all rights reserved).
    Psychological Assessment 09/2015; 27(3):932-943. DOI:10.1037/pas0000091 · 2.99 Impact Factor
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    ABSTRACT: People with larger brains tend to score higher on tests of general intelligence (g). It is unclear, however, how much variance in intelligence other brain measurements would account for if included together with brain volume in a multivariable model. We examined a large sample of individuals in their seventies (n = 672) who were administered a comprehensive cognitive test battery. Using structural equation modelling, we related six common magnetic resonance imaging-derived brain variables that represent normal and abnormal features—brain volume, cortical thickness, white matter structure, white matter hyperintensity load, iron deposits, and microbleeds—to g and to fluid intelligence. As expected, brain volume accounted for the largest portion of variance (~ 12%, depending on modelling choices). Adding the additional variables, especially cortical thickness (+~ 5%) and white matter hyperintensity load (+~ 2%), increased the predictive value of the model. Depending on modelling choices, all neuroimaging variables together accounted for 18–21% of the variance in intelligence. These results reveal which structural brain imaging measures relate to g over and above the largest contributor, total brain volume. They raise questions regarding which other neuroimaging measures might account for even more of the variance in intelligence.
    Intelligence 08/2015; 51. DOI:10.1016/j.intell.2015.05.001 · 2.67 Impact Factor
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    ABSTRACT: Cognitive decline, especially the slowing of information processing speed, is associated with normal ageing. This decline may be due to brain cortico-cortical disconnection caused by age-related white matter deterioration. We present results from a large, narrow age range cohort of generally healthy, community-dwelling subjects in their seventies who also had their cognitive ability tested in youth (age 11 years). We investigate associations between older age brain white matter structure, several measures of information processing speed and childhood cognitive ability in 581 subjects. Analysis of diffusion tensor MRI data using Tract-based Spatial Statistics (TBSS) showed that all measures of information processing speed, as well as a general speed factor composed from these tests (g speed), were significantly associated with fractional anisotropy (FA) across the white matter skeleton rather than in specific tracts. Cognitive ability measured at age 11 years was not associated with older age white matter FA, except for the g speed-independent components of several individual processing speed tests. These results indicate that quicker and more efficient information processing requires global connectivity in older age, and that associations between white matter FA and information processing speed (both individual test scores and g speed), unlike some other aspects of later life brain structure, are generally not accounted for by cognitive ability measured in youth.
    Brain Structure and Function 08/2015; DOI:10.1007/s00429-015-1097-5 · 4.57 Impact Factor
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    ABSTRACT: Cognitive deficits and reduced educational achievement are common in psychiatric illness; understanding the genetic basis of cognitive and educational deficits may be informative about the etiology of psychiatric disorders. A recent, large genome-wide association study (GWAS) reported a genome-wide significant locus for years of education, which subsequently demonstrated association to general cognitive ability ("g") in overlapping cohorts. The current study was designed to test whether GWAS hits for educational attainment are involved in general cognitive ability in an independent, large-scale collection of cohorts. Using cohorts in the Cognitive Genomics Consortium (COGENT; up to 20,495 healthy individuals), we examined the relationship between g and variants associated with educational attainment. We next conducted meta-analyses with 24,189 individuals with neurocognitive data from the educational attainment studies, and then with 53,188 largely independent individuals from a recent GWAS of cognition. A SNP (rs1906252) located at chromosome 6q16.1, previously associated with years of schooling, was significantly associated with g (P = 1.47 × 10(-4) ) in COGENT. The first joint analysis of 43,381 non-overlapping individuals for this a priori-designated locus was strongly significant (P = 4.94 × 10(-7) ), and the second joint analysis of 68,159 non-overlapping individuals was even more robust (P = 1.65 × 10(-9) ). These results provide independent replication, in a large-scale dataset, of a genetic locus associated with cognitive function and education. As sample sizes grow, cognitive GWAS will identify increasing numbers of associated loci, as has been accomplished in other polygenic quantitative traits, which may be relevant to psychiatric illness. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.
    American Journal of Medical Genetics Part B Neuropsychiatric Genetics 07/2015; 168(5). DOI:10.1002/ajmg.b.32319 · 3.27 Impact Factor
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    ABSTRACT: Homozygosity has long been associated with rare, often devastating, Mendelian disorders1, and Darwin was one of the first to recognize that inbreeding reduces evolutionary fitness2. However, the effect of the more distant parental relatedness that is common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power3, 4. Here we use runs of homozygosity to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts, and find statistically significant associations between summed runs of homozygosity and four complex traits: height, forced expiratory lung volume in one second, general cognitive ability and educational attainment (P < 1 × 10−300, 2.1 × 10−6, 2.5 × 10−10 and 1.8 × 10−10, respectively). In each case, increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months’ less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing evidence that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples5, 6, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection7, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been.
    Nature 07/2015; DOI:10.1038/nature14618 · 42.35 Impact Factor
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    ABSTRACT: Cerebral small vessel disease (SVD) may cause cognitive dysfunction. We tested the association between the combined presence of magnetic resonance imaging (MRI) features of SVD and cognitive ability in older age. Cognitive testing and brain MRI were performed in 680 older participants. MRI presence of lacunes, white matter hyperintensities, microbleeds, and perivascular spaces were summed in a score of 0-4 representing all SVD features combined. We also applied latent variable modeling to test whether the 4 MRI features form a unitary SVD construct. The SVD score showed significant associations with general cognitive ability. Latent variable modeling indicated that the 4 MRI markers formed a unitary construct, which showed consistent associations with cognitive ability compared with the SVD score. Total MRI load of SVD is associated with lower general cognitive ability in older age. The total SVD score performed consistently with the more complex latent variable model, suggesting validity and potential utility in future research for determining total SVD load. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
    Neurobiology of aging 06/2015; DOI:10.1016/j.neurobiolaging.2015.06.024 · 4.85 Impact Factor
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    ABSTRACT: We tested whether DNA-methylation profiles account for inter-individual variation in body mass index (BMI) and height and whether they predict these phenotypes over and above genetic factors. Genetic predictors were derived from published summary results from the largest genome-wide association studies on BMI (n ∼ 350,000) and height (n ∼ 250,000) to date. We derived methylation predictors by estimating probe-trait effects in discovery samples and tested them in external samples. Methylation profiles associated with BMI in older individuals from the Lothian Birth Cohorts (LBCs, n = 1,366) explained 4.9% of the variation in BMI in Dutch adults from the LifeLines DEEP study (n = 750) but did not account for any BMI variation in adolescents from the Brisbane Systems Genetic Study (BSGS, n = 403). Methylation profiles based on the Dutch sample explained 4.9% and 3.6% of the variation in BMI in the LBCs and BSGS, respectively. Methylation profiles predicted BMI independently of genetic profiles in an additive manner: 7%, 8%, and 14% of variance of BMI in the LBCs were explained by the methylation predictor, the genetic predictor, and a model containing both, respectively. The corresponding percentages for LifeLines DEEP were 5%, 9%, and 13%, respectively, suggesting that the methylation profiles represent environmental effects. The differential effects of the BMI methylation profiles by age support previous observations of age modulation of genetic contributions. In contrast, methylation profiles accounted for almost no variation in height, consistent with a mainly genetic contribution to inter-individual variation. The BMI results suggest that combining genetic and epigenetic information might have greater utility for complex-trait prediction. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.
    The American Journal of Human Genetics 06/2015; 97(1). DOI:10.1016/j.ajhg.2015.05.014 · 10.99 Impact Factor
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    ABSTRACT: Fibrinogen, coagulation factor VII (FVII), factor VIII (FVIII), and its carrier von Willebrand factor (vWF) play key roles in hemostasis. Previously identified common variants explain only a small fraction of the trait heritabilities and additional variation may be explained by associations with rarer variants with larger effects. The aim of this study was to identify low-frequency (minor allele frequency [MAF] ≥0.01 and <0.05) and rare (MAF <0.01) variants that influence plasma concentrations of these 4 hemostatic factors by meta-analyzing exome chip data from up to 76,000 participants of 4 ancestries. We identified 12 novel associations of low-frequency (n=2) and rare (n=10) variants across the fibrinogen, FVII, FVIII, and vWF traits that were independent of previously identified associations. Novel loci were found within previously reported genes and had effect sizes much larger than and independent of previously identified common variants. In addition, associations at KCNT1, HID1, and KATNB1 identify new candidate genes related to hemostasis for follow-up replication and functional genomic analysis. Newly identified low-frequency and rare-variant associations accounted for modest amounts of trait variance and therefore are unlikely to increase predicted trait heritability but provide new information to understanding individual variation in hemostasis pathways. Copyright © 2015 American Society of Hematology.
    Blood 06/2015; DOI:10.1182/blood-2015-02-624551 · 10.43 Impact Factor
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    ABSTRACT: Inactive lifestyles have negative health consequences, while time spent sedentary (sitting and lying) is related to morbidity and premature mortality. Older adults often form the most sedentary segment of the population. Much of this behaviour may be practised at home where this group can spend extended periods. Physical activity rates among older adults are particularly low. Even household physical activities can be beneficial for this group, while they can constitute much of an older person's total activity. Despite this context, the home's role in the active and sedentary behaviours of the older population appears critically understudied. Using interview and focus group data collected from 22 older adults (healthy volunteers, stroke survivors and people with dementia), this paper begins to address this issue. Aspects of the home that aid or impede a more active, less sedentary lifestyle are identified with three presenting particular capacity in this respect discussed: steps, space within the home, and the location and form of facilities, fixtures and fittings. The crucial role health status plays in structuring this capacity is identified. Simple design recommendations, devised to support older people to lead more active lives at home, are presented.
    Building Research and Information 06/2015; 43(5):1-15. DOI:10.1080/09613218.2015.1045702 · 1.32 Impact Factor
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    ABSTRACT: Understanding aging-related cognitive decline is of growing importance in aging societies, but relatively little is known about its neural substrates. Measures of white matter microstructure are known to correlate cross-sectionally with cognitive ability measures, but only a few small studies have tested for longitudinal relations among these variables. We tested whether there were coupled changes in brain white matter microstructure indexed by fractional anisotropy (FA) and three broad cognitive domains (fluid intelligence, processing speed, and memory) in a large cohort of human participants with longitudinal diffusion tensor MRI and detailed cognitive data taken at ages 73 years (n = 731) and 76 years (n = 488). Longitudinal changes in white matter microstructure were coupled with changes in fluid intelligence, but not with processing speed or memory. Individuals with higher baseline white matter FA showed less subsequent decline in processing speed. Our results provide evidence for a longitudinal link between changes in white matter microstructure and aging-related cognitive decline during the eighth decade of life. They are consistent with theoretical perspectives positing that a corticocortical "disconnection" partly explains cognitive aging. Copyright © 2015 Ritchie et al.
    The Journal of Neuroscience : The Official Journal of the Society for Neuroscience 06/2015; 35(22):8672-82. DOI:10.1523/JNEUROSCI.0862-15.2015 · 6.75 Impact Factor
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    ABSTRACT: Neuroticism is a pervasive risk factor for psychiatric conditions. It genetically overlaps with major depressive disorder (MDD) and is therefore an important phenotype for psychiatric genetics. The Genetics of Personality Consortium has created a resource for genome-wide association analyses of personality traits in more than 63 000 participants (including MDD cases). To identify genetic variants associated with neuroticism by performing a meta-analysis of genome-wide association results based on 1000 Genomes imputation; to evaluate whether common genetic variants as assessed by single-nucleotide polymorphisms (SNPs) explain variation in neuroticism by estimating SNP-based heritability; and to examine whether SNPs that predict neuroticism also predict MDD. Genome-wide association meta-analysis of 30 cohorts with genome-wide genotype, personality, and MDD data from the Genetics of Personality Consortium. The study included 63 661 participants from 29 discovery cohorts and 9786 participants from a replication cohort. Participants came from Europe, the United States, or Australia. Analyses were conducted between 2012 and 2014. Neuroticism scores harmonized across all 29 discovery cohorts by item response theory analysis, and clinical MDD case-control status in 2 of the cohorts. A genome-wide significant SNP was found on 3p14 in MAGI1 (rs35855737; P = 9.26 × 10-9 in the discovery meta-analysis). This association was not replicated (P = .32), but the SNP was still genome-wide significant in the meta-analysis of all 30 cohorts (P = 2.38 × 10-8). Common genetic variants explain 15% of the variance in neuroticism. Polygenic scores based on the meta-analysis of neuroticism in 27 cohorts significantly predicted neuroticism (1.09 × 10-12 < P < .05) and MDD (4.02 × 10-9 < P < .05) in the 2 other cohorts. This study identifies a novel locus for neuroticism. The variant is located in a known gene that has been associated with bipolar disorder and schizophrenia in previous studies. In addition, the study shows that neuroticism is influenced by many genetic variants of small effect that are either common or tagged by common variants. These genetic variants also influence MDD. Future studies should confirm the role of the MAGI1 locus for neuroticism and further investigate the association of MAGI1 and the polygenic association to a range of other psychiatric disorders that are phenotypically correlated with neuroticism.
    JAMA Psychiatry 05/2015; 72(7). DOI:10.1001/jamapsychiatry.2015.0554 · 12.01 Impact Factor
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    ABSTRACT: The Addenbrooke's Cognitive Examination (ACE) is used to measure cognition across a range of domains in dementia. Identifying the order in which cognitive decline occurs across items, and whether this varies between dementia aetiologies could add more information to subdomain scores. ACE-Revised data from 350 patients were split into three groups: Alzheimer's type (n = 131), predominantly frontal (n = 119) and other frontotemporal lobe degenerative disorders (n = 100). Results of factor analysis and Mokken scaling analysis were compared. Principal component analysis revealed one factor for each group. Confirmatory factor analysis found that the one-factor model fit two samples poorly. Mokken analyses revealed different item ordering in terms of difficulty for each group. The different patterns for each diagnostic group could aid in the separation of these different types of dementia.
    05/2015; 5(1):155-69. DOI:10.1159/000375364
  • PLoS ONE 04/2015; 10(4):e0125280. DOI:10.1371/journal.pone.0125280 · 3.23 Impact Factor
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    Molecular Psychiatry 04/2015; · 15.15 Impact Factor
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    ABSTRACT: To identify common variants contributing to normal variation in two specific domains of cognitive functioning, we conducted a genome-wide association study (GWAS) of executive functioning and information processing speed in non-demented older adults from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) consortium. Neuropsychological testing was available for 5429-32 070 subjects of European ancestry aged 45 years or older, free of dementia and clinical stroke at the time of cognitive testing from 20 cohorts in the discovery phase. We analyzed performance on the Trail Making Test parts A and B, the Letter Digit Substitution Test (LDST), the Digit Symbol Substitution Task (DSST), semantic and phonemic fluency tests, and the Stroop Color and Word Test. Replication was sought in 1311-21860 subjects from 20 independent cohorts. A significant association was observed in the discovery cohorts for the single-nucleotide polymorphism (SNP) rs17518584 (discovery P-value=3.12 × 10(-8)) and in the joint discovery and replication meta-analysis (P-value=3.28 × 10(-9) after adjustment for age, gender and education) in an intron of the gene cell adhesion molecule 2 (CADM2) for performance on the LDST/DSST. Rs17518584 is located about 170 kb upstream of the transcription start site of the major transcript for the CADM2 gene, but is within an intron of a variant transcript that includes an alternative first exon. The variant is associated with expression of CADM2 in the cingulate cortex (P-value=4 × 10(-4)). The protein encoded by CADM2 is involved in glutamate signaling (P-value=7.22 × 10(-15)), gamma-aminobutyric acid (GABA) transport (P-value=1.36 × 10(-11)) and neuron cell-cell adhesion (P-value=1.48 × 10(-13)). Our findings suggest that genetic variation in the CADM2 gene is associated with individual differences in information processing speed.Molecular Psychiatry advance online publication, 14 April 2015; doi:10.1038/mp.2015.37.
    Molecular Psychiatry 04/2015; DOI:10.1038/mp.2015.37 · 15.15 Impact Factor
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    PLoS ONE 04/2015; 10(4):e0123886. DOI:10.1371/journal.pone.0123886 · 3.23 Impact Factor
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    ABSTRACT: Cerebral microvascular disease is associated with dementia. Differences in the topography of the retinal vascular network may be a marker for cerebrovascular disease. The association between cerebral microvascular state and non-pathological cognitive ageing is less clear, particularly because studies are rarely able to adjust for pre-morbid cognitive ability level. We measured retinal vascular fractal dimension (Df) as a potential marker of cerebral microvascular disease. We examined the extent to which it contributes to differences in non-pathological cognitive ability in old age, after adjusting for childhood mental ability. Participants from the Lothian Birth Cohort 1936 Study (LBC1936) had cognitive ability assessments and retinal photographs taken of both eyes aged around 73 years (n = 648). IQ scores were available from childhood. Retinal vascular Df was calculated with monofractal and multifractal analysis, performed on custom-written software. Multiple regression models were applied to determine associations between retinal vascular Df and general cognitive ability (g), processing speed, and memory. Only three out of 24 comparisons (two eyes × four Df parameters × three cognitive measures) were found to be significant. This is little more than would be expected by chance. No single association was verified by an equivalent association in the contralateral eye. The results show little evidence that fractal measures of retinal vascular differences are associated with non-pathological cognitive ageing.
    PLoS ONE 03/2015; 10(3):e0121119. DOI:10.1371/journal.pone.0121119 · 3.23 Impact Factor
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    ABSTRACT: Cognitive impairment is common among individuals diagnosed with autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD). It has been suggested that some aspects of intelligence are preserved or even superior in people with ASD compared with controls, but consistent evidence is lacking. Few studies have examined the genetic overlap between cognitive ability and ASD/ADHD. The aim of this study was to examine the polygenic overlap between ASD/ADHD and cognitive ability in individuals from the general population. Polygenic risk for ADHD and ASD was calculated from genome-wide association studies of ASD and ADHD conducted by the Psychiatric Genetics Consortium. Risk scores were created in three independent cohorts: Generation Scotland Scottish Family Health Study (GS:SFHS) (n=9863), the Lothian Birth Cohorts 1936 and 1921 (n=1522), and the Brisbane Adolescent Twin Sample (BATS) (n=921). We report that polygenic risk for ASD is positively correlated with general cognitive ability (beta=0.07, P=6 × 10(-7), r(2)=0.003), logical memory and verbal intelligence in GS:SFHS. This was replicated in BATS as a positive association with full-scale intelligent quotient (IQ) (beta=0.07, P=0.03, r(2)=0.005). We did not find consistent evidence that polygenic risk for ADHD was associated with cognitive function; however, a negative correlation with IQ at age 11 years (beta=-0.08, Z=-3.3, P=0.001) was observed in the Lothian Birth Cohorts. These findings are in individuals from the general population, suggesting that the relationship between genetic risk for ASD and intelligence is partly independent of clinical state. These data suggest that common genetic variation relevant for ASD influences general cognitive ability.Molecular Psychiatry advance online publication, 10 March 2015; doi:10.1038/mp.2015.12.
    Molecular Psychiatry 03/2015; DOI:10.1038/mp.2015.12 · 15.15 Impact Factor
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    ABSTRACT: The degree to which genetic factors influence brain connectivity is beginning to be understood. Large-scale efforts are underway to map the profile of genetic effects in various brain regions. The NIH-funded Human Connectome Project (HCP) is providing data valuable for analyzing the degree of genetic influence underlying brain connectivity revealed by state-of-the-art neuroimaging methods. We calculated the heritability of the fractional anisotropy (FA) measure derived from diffusion tensor imaging (DTI) reconstruction in 481 HCP subjects (194/287M/F) consisting of 57/60 pairs of mono- and dizygotic twins, and 246 siblings. FA measurements were derived using (Enhancing NeuroImaging Genetics through Meta-Analysis) ENIGMA DTI protocols and heritability estimates were calculated using the SOLAR-Eclipse imaging genetic analysis package. We compared heritability estimates derived from HCP data to those publicly available through the ENIGMA-DTI consortium, which were pooled together from five-family based studies across the US, Europe, and Australia. FA measurements from the HCP cohort for eleven major white matter tracts were highly heritable (h(2)=0.53-0.90, p<10(-5)), and were significantly correlated with the joint-analytical estimates from the ENIGMA cohort on the tract and voxel-wise levels. The similarity in regional heritability suggests that the additive genetic contribution to white matter microstructure is consistent across populations and imaging acquisition parameters. It also suggests the overarching genetic influence provides an opportunity to define a common genetic search space for future gene-discovery studies. Uniquely, the measurements of additive genetic contribution performed in this study can be repeated using online genetic analysis tools provided by the HCP ConnectomeDB web application. Copyright © 2015 Elsevier Inc. All rights reserved.
    NeuroImage 03/2015; 111. DOI:10.1016/j.neuroimage.2015.02.050 · 6.36 Impact Factor

Publication Stats

10k Citations
2,718.31 Total Impact Points


  • 1996–2015
    • The University of Edinburgh
      • • Centre for Cognitive Ageing and Cognitive Epidemiology
      • • Department of Psychology
      • • Department of Geriatric Medicine
      Edinburgh, Scotland, United Kingdom
  • 2014
    • The UK Clinical Virology Network
      Edinburgh, Scotland, United Kingdom
  • 2013
    • University of Bristol
      • School of Social and Community Medicine
      Bristol, England, United Kingdom
    • NHS Lothian
      Edinburgh, Scotland, United Kingdom
    • Heriot-Watt University
      Edinburgh, Scotland, United Kingdom
  • 1996–2011
    • University of Aberdeen
      • • School of Psychology
      • • Department of Radiology
      Aberdeen, Scotland, United Kingdom
  • 2008
    • Victoria General Hospital
      Winnipeg, Manitoba, Canada
  • 1998–2007
    • Royal Berkshire NHS Foundation Trust
      Reading, England, United Kingdom
  • 1992–2007
    • The Royal Observatory, Edinburgh
      Edinburgh, Scotland, United Kingdom
  • 2003
    • University of Glasgow
      Glasgow, Scotland, United Kingdom
  • 1994–1996
    • Ealing, Hammersmith & West London College
      Londinium, England, United Kingdom
    • Bristol-Myers Squibb
      New York, New York, United States