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Structural brain abnormalities have been described in autism but studies are often small and contradictory. We aimed to identify which brain regions can reliably be regarded as different in autism compared to healthy controls.
A systematic search was conducted for magnetic resonance imaging studies of regional brain size in autism. Data were extracted and combined using random effects meta-analysis. The modifying effects of age and IQ were investigated using meta-regression.
The total brain, cerebral hemispheres, cerebellum and caudate nucleus were increased in volume, whereas the corpus callosum area was reduced. There was evidence for a modifying effect of age and IQ on the cerebellar vermal lobules VI–VII and for age on the amygdala.
Autism may result from abnormalities in specific brain regions and a global lack of integration due to brain enlargement. Inconsistencies in the literature partly relate to differences in the age and IQ of study populations. Some regions may show abnormal growth trajectories.
Cognitive impairment associated with lifetime major depressive disorder (MDD) is well-supported by meta-analytic studies, but population-based estimates remain scarce. Previous UK Biobank studies have only shown limited evidence of cognitive differences related to probable MDD. Using updated cognitive and clinical assessments in UK Biobank, this study investigated population-level differences in cognitive functioning associated with lifetime MDD.
Associations between lifetime MDD and cognition (performance on six tasks and general cognitive functioning [g-factor]) were investigated in UK Biobank (N-range 7,457–14,836, age 45–81 years, 52% female), adjusting for demographics, education, and lifestyle. Lifetime MDD classifications were based on the Composite International Diagnostic Interview. Within the lifetime MDD group, we additionally investigated relationships between cognition and (a) recurrence, (b) current symptoms, (c) severity of psychosocial impairment (while symptomatic), and (d) concurrent psychotropic medication use.
Lifetime MDD was robustly associated with a lower g-factor (β = −0.10, PFDR = 4.7 × 10−5), with impairments in attention, processing speed, and executive functioning (β ≥ 0.06). Clinical characteristics revealed differential profiles of cognitive impairment among case individuals; those who reported severe psychosocial impairment and use of psychotropic medication performed worse on cognitive tests. Severe psychosocial impairment and reasoning showed the strongest association (β = −0.18, PFDR = 7.5 × 10−5).
Findings describe small but robust associations between lifetime MDD and lower cognitive performance within a population-based sample. Overall effects were of modest effect size, suggesting limited clinical relevance. However, deficits within specific cognitive domains were more pronounced in relation to clinical characteristics, particularly severe psychosocial impairment.
UK Biobank is a well-characterised cohort of over 500 000 participants including genetics, environmental data and imaging. An online mental health questionnaire was designed for UK Biobank participants to expand its potential.
Describe the development, implementation and results of this questionnaire.
An expert working group designed the questionnaire, using established measures where possible, and consulting a patient group. Operational criteria were agreed for defining likely disorder and risk states, including lifetime depression, mania/hypomania, generalised anxiety disorder, unusual experiences and self-harm, and current post-traumatic stress and hazardous/harmful alcohol use.
A total of 157 366 completed online questionnaires were available by August 2017. Participants were aged 45–82 (53% were ≥65 years) and 57% women. Comparison of self-reported diagnosed mental disorder with a contemporary study shows a similar prevalence, despite respondents being of higher average socioeconomic status. Lifetime depression was a common finding, with 24% (37 434) of participants meeting criteria and current hazardous/harmful alcohol use criteria were met by 21% (32 602), whereas other criteria were met by less than 8% of the participants. There was extensive comorbidity among the syndromes. Mental disorders were associated with a high neuroticism score, adverse life events and long-term illness; addiction and bipolar affective disorder in particular were associated with measures of deprivation.
The UK Biobank questionnaire represents a very large mental health survey in itself, and the results presented here show high face validity, although caution is needed because of selection bias. Built into UK Biobank, these data intersect with other health data to offer unparalleled potential for crosscutting biomedical research involving mental health.
Studies suggest that alcohol consumption and alcohol use disorders have distinct genetic backgrounds.
We examined whether polygenic risk scores (PRS) for consumption and problem subscales of the Alcohol Use Disorders Identification Test (AUDIT-C, AUDIT-P) in the UK Biobank (UKB; N = 121 630) correlate with alcohol outcomes in four independent samples: an ascertained cohort, the Collaborative Study on the Genetics of Alcoholism (COGA; N = 6850), and population-based cohorts: Avon Longitudinal Study of Parents and Children (ALSPAC; N = 5911), Generation Scotland (GS; N = 17 461), and an independent subset of UKB (N = 245 947). Regression models and survival analyses tested whether the PRS were associated with the alcohol-related outcomes.
In COGA, AUDIT-P PRS was associated with alcohol dependence, AUD symptom count, maximum drinks (R2 = 0.47–0.68%, p = 2.0 × 10−8–1.0 × 10−10), and increased likelihood of onset of alcohol dependence (hazard ratio = 1.15, p = 4.7 × 10−8); AUDIT-C PRS was not an independent predictor of any phenotype. In ALSPAC, the AUDIT-C PRS was associated with alcohol dependence (R2 = 0.96%, p = 4.8 × 10−6). In GS, AUDIT-C PRS was a better predictor of weekly alcohol use (R2 = 0.27%, p = 5.5 × 10−11), while AUDIT-P PRS was more associated with problem drinking (R2 = 0.40%, p = 9.0 × 10−7). Lastly, AUDIT-P PRS was associated with ICD-based alcohol-related disorders in the UKB subset (R2 = 0.18%, p < 2.0 × 10−16).
AUDIT-P PRS was associated with a range of alcohol-related phenotypes across population-based and ascertained cohorts, while AUDIT-C PRS showed less utility in the ascertained cohort. We show that AUDIT-P is genetically correlated with both use and misuse and demonstrate the influence of ascertainment schemes on PRS analyses.
Major depressive disorder and neuroticism (Neu) share a large genetic basis. We sought to determine whether this shared basis could be decomposed to identify genetic factors that are specific to depression.
We analysed summary statistics from genome-wide association studies (GWAS) of depression (from the Psychiatric Genomics Consortium, 23andMe and UK Biobank) and compared them with GWAS of Neu (from UK Biobank). First, we used a pairwise GWAS analysis to classify variants as associated with only depression, with only Neu or with both. Second, we estimated partial genetic correlations to test whether the depression's genetic link with other phenotypes was explained by shared overlap with Neu.
We found evidence that most genomic regions (25/37) associated with depression are likely to be shared with Neu. The overlapping common genetic variance of depression and Neu was genetically correlated primarily with psychiatric disorders. We found that the genetic contributions to depression, that were not shared with Neu, were positively correlated with metabolic phenotypes and cardiovascular disease, and negatively correlated with the personality trait conscientiousness. After removing shared genetic overlap with Neu, depression still had a specific association with schizophrenia, bipolar disorder, coronary artery disease and age of first birth. Independent of depression, Neu had specific genetic correlates in ulcerative colitis, pubertal growth, anorexia and education.
Our findings demonstrate that, while genetic risk factors for depression are largely shared with Neu, there are also non-Neu-related features of depression that may be useful for further patient or phenotypic stratification.
Substantial clinical heterogeneity of major depressive disorder (MDD) suggests it may group together individuals with diverse aetiologies. Identifying distinct subtypes should lead to more effective diagnosis and treatment, while providing more useful targets for further research. Genetic and clinical overlap between MDD and schizophrenia (SCZ) suggests an MDD subtype may share underlying mechanisms with SCZ.
The present study investigated whether a neurobiologically distinct subtype of MDD could be identified by SCZ polygenic risk score (PRS). We explored interactive effects between SCZ PRS and MDD case/control status on a range of cortical, subcortical and white matter metrics among 2370 male and 2574 female UK Biobank participants.
There was a significant SCZ PRS by MDD interaction for rostral anterior cingulate cortex (RACC) thickness (β = 0.191, q = 0.043). This was driven by a positive association between SCZ PRS and RACC thickness among MDD cases (β = 0.098, p = 0.026), compared to a negative association among controls (β = −0.087, p = 0.002). MDD cases with low SCZ PRS showed thinner RACC, although the opposite difference for high-SCZ-PRS cases was not significant. There were nominal interactions for other brain metrics, but none remained significant after correcting for multiple comparisons.
Our significant results indicate that MDD case-control differences in RACC thickness vary as a function of SCZ PRS. Although this was not the case for most other brain measures assessed, our specific findings still provide some further evidence that MDD in the presence of high genetic risk for SCZ is subtly neurobiologically distinct from MDD in general.
Background: Cervical spondylotic myelopathy (CSM) is the leading cause of spinal cord impairment. In a public healthcare system, wait times to see spine specialists and eventually access surgical treatment for CSM can be substantial. The goals of this study were to determine consultation wait times (CWT) and surgical wait times (SWT), and identify predictors of wait time length. Methods: Consecutive patients enrolled in the Canadian Spine Outcomes and Research Network (CSORN) prospective and observational CSM study from March 2015 to July 2017 were included. A data-splitting technique was used to develop and internally validate multivariable models of potential predictors. Results: A CSORN query returned 264 CSM patients for CWT. The median was 46 days. There were 31% mild, 35% moderate, and 33% severe CSM. There was a statistically significant difference in median CWT between moderate and severe groups; 207 patients underwent surgical treatment. Median SWT was 42 days. There was a statistically significant difference in SWT between mild/moderate and severe groups. Short symptom duration, less pain, lower BMI, and lower physical component score of SF-12 were predictive of shorter CWT. Only baseline pain and medication duration were predictive of SWT. Both CWT and SWT were shorter compared to a concurrent cohort of lumbar stenosis patients (p <0.001). Conclusions: Patients with shorter duration (either symptoms or medication) and less neck pain waited less to see a spine specialist in Canada and to undergo surgical treatment. This study highlights some of the obstacles to overcome in expedited care for this patient population.
An increasing body of genetic and imaging research shows that it is becoming possible to forecast the onset of major psychiatric disorders such as depression and schizophrenia before people become ill with ever improving accuracy. Practical issues such as the optimal combination of clinical and biological variables are being addressed, but the application of predictive algorithms to individuals or in routine clinical settings have yet to be tested. The development of predictive methods in mental health comes with substantial ethical questions, including whether people wish to know their level of risk, as well as individual and societal attitudes to the potential adverse effects of data sharing, early diagnosis and treatment, which so far have been largely ignored. Preliminary data suggests that at least some people think predictive research is valuable and would take part in such studies, and some would welcome knowing the results. Future initiatives should systematically assess opinions and attitudes in conjunction with scientific and technical advances.
Declaration of interest
In the past 3 years, S.M.L. has received personal fees from Otsuaka, Sunovion and Janssen, and research grant support from Janssen and Lundbeck. A.M.M. has received research support from the Sackler Trust, Eli Lilly and Janssen. S.M.L. is part of the PSYSCAN consortium.
There is increasing evidence for shared genetic susceptibility between schizophrenia and bipolar disorder. Although genetic variants only convey subtle increases in risk individually, their combination into a polygenic risk score constitutes a strong disease predictor.
To investigate whether schizophrenia and bipolar disorder polygenic risk scores can distinguish people with broadly defined psychosis and their unaffected relatives from controls.
Using the latest Psychiatric Genomics Consortium data, we calculated schizophrenia and bipolar disorder polygenic risk scores for 1168 people with psychosis, 552 unaffected relatives and 1472 controls.
Patients with broadly defined psychosis had dramatic increases in schizophrenia and bipolar polygenic risk scores, as did their relatives, albeit to a lesser degree. However, the accuracy of predictive models was modest.
Although polygenic risk scores are not ready for clinical use, it is hoped that as they are refined they could help towards risk reduction advice and early interventions for psychosis.
Declaration of interest
R.M.M. has received honoraria for lectures from Janssen, Lundbeck, Lilly, Otsuka and Sunovian.
UK Biobank is a well-characterised cohort of over 500 000 participants that offers unique opportunities to investigate multiple diseases and risk factors.
An online mental health questionnaire completed by UK Biobank participants was expected to expand the potential for research into mental disorders.
An expert working group designed the questionnaire, using established measures where possible, and consulting with a patient group regarding acceptability. Case definitions were defined using operational criteria for lifetime depression, mania, anxiety disorder, psychotic-like experiences and self-harm, as well as current post-traumatic stress and alcohol use disorders.
157 366 completed online questionnaires were available by August 2017. Comparison of self-reported diagnosed mental disorder with a contemporary study shows a similar prevalence, despite respondents being of higher average socioeconomic status than the general population across a range of indicators. Thirty-five per cent (55 750) of participants had at least one defined syndrome, of which lifetime depression was the most common at 24% (37 434). There was extensive comorbidity among the syndromes. Mental disorders were associated with high neuroticism score, adverse life events and long-term illness; addiction and bipolar affective disorder in particular were associated with measures of deprivation.
The questionnaire represents a very large mental health survey in itself, and the results presented here show high face validity, although caution is needed owing to selection bias. Built into UK Biobank, these data intersect with other health data to offer unparalleled potential for crosscutting biomedical research involving mental health.
Declaration of interest
G.B. received grants from the National Institute for Health Research during the study; and support from Illumina Ltd. and the European Commission outside the submitted work. B.C. received grants from the Scottish Executive Chief Scientist Office and from The Dr Mortimer and Theresa Sackler Foundation during the study. C.S. received grants from the Medical Research Council and Wellcome Trust during the study, and is the Chief Scientist for UK Biobank. M.H. received grants from the Innovative Medicines Initiative via the RADAR-CNS programme and personal fees as an expert witness outside the submitted work.
Low birth weight has been inconsistently associated with risk of
developing affective disorders, including major depressive disorder
(MDD). To date, studies investigating possible associations between birth
weight and bipolar disorder (BD), or personality traits known to
predispose to affective disorders such as neuroticism, have not been
conducted in large cohorts.
To assess whether very low birth weight (<1500 g) and low birth weight
(1500–2490 g) were associated with higher neuroticism scores assessed in
middle age, and lifetime history of either MDD or BD. We controlled for
possible confounding factors.
Retrospective cohort study using baseline data on the 83 545 UK Biobank
participants with detailed mental health and birth weight data. Main
outcomes were prevalent MDD and BD, and neuroticism assessed using the
Eysenck Personality Inventory Neuroticism scale - Revised (EPIN-R)
Referent to normal birth weight, very low/low birth weight were
associated with higher neuroticism scores, increased MDD and BD. The
associations between birth weight category and MDD were partially
mediated by higher neuroticism.
These findings suggest that intrauterine programming may play a role in
lifetime vulnerability to affective disorders.
California and Washington recently replaced traditional partisan elections with nonpartisan “top-two” election procedures. Some reform advocates hoped that voters would behave in a way to support moderate candidates in the primary stage; the limited evidence for this behaviour has led some scholars to conclude that the reform has little chance to change meaningful policy outcomes. Yet we find that the nonpartisan procedure has predictable and disparate political consequences: the general elections between two candidates of the same party, called copartisan general elections, tend to occur in districts without any meaningful crossparty competition. Furthermore, copartisan elections are more likely to occur with open seats, when a new legislator will begin building a network of relationships. The results, viewed through the lens of the Advocacy Coalition Framework, suggest that opportunities exist for coalitional rearrangement over time.
The relative contribution of demographic, lifestyle and medication factors to the association between affective disorders and cardiometabolic diseases is poorly understood.
To assess the relationship between cardiometabolic disease and features of depresion and bipolar disorder within a large population sample.
Cross-sectional study of 145 991 UK Biobank participants: multivariate analyses of associations between features of depression or bipolar disorder and five cardiometabolic outcomes, adjusting for confounding factors.
There were significant associations between mood disorder features and ‘any cardiovascular disease’ (depression odds ratio (OR) = 1.15, 95% CI 1.12–1.19; bipolar OR = 1.28, 95% CI 1.14–1.43) and with hypertension (depression OR = 1.15, 95% CI 1.13–1.18; bipolar OR = 1.26, 95% CI 1.12–1.42). Individuals with features of mood disorder taking psychotropic medication were significantly more likely than controls not on psychotropics to report myocardial infarction (depression OR = 1.47, 95% CI 1.24–1.73; bipolar OR = 2.23, 95% CI 1.53–3.57) and stroke (depression OR = 2.46, 95% CI 2.10–2.80; bipolar OR = 2.31, 95% CI 1.39–3.85).
Associations between features of depression or bipolar disorder and cardiovascular disease outcomes were statistically independent of demographic, lifestyle and medication confounders. Psychotropic medication may also be a risk factor for cardiometabolic disease in individuals without a clear history of mood disorder.
Structural and functional magnetic resonance imaging (MRI) of patients with psychosis has advanced to the point where there are clear abnormalities at a group level between patients and groups of healthy controls, and suggestions of different patterns of abnormalities between groups of patients. A major area of research endeavour is being able to translate these group differences into clinically relevant predictions at an individual patient level. Here, we briefly summarize our main findings in cohorts at high risk of psychosis because they come from families in which several members have schizophrenia or bipolar disorder, or have educational impairments. We highlight consistent predictors of psychosis in those at high risk of schizophrenia for genetic or cognitive reasons, as compared with quite distinct profiles between those at genetic high risk of schizophrenia v. bipolar disorder on functional MRI during an executive language task. We also consider future research directions and ethical issues in the early diagnostic testing of people at high risk of psychosis.
A masked analysis of videotaped assessments of people at high genetic risk of schizophrenia revealed that those who subsequently went on to develop schizophrenia used significantly more second-person pronouns. This was evident before diagnosis, at two separate assessments approximately 18 months apart. This supports the view that people who go on to develop schizophrenia may have an abnormality in the deictic frame of interpersonal communication – that is, the distinction between concepts being self-generated or from elsewhere may be blurred prior to the onset of a diagnosis of schizophrenia.
No longitudinal study has yet examined the association between substance use and brain volume changes in a population at high risk of schizophrenia.
To examine the effects of cannabis on longitudinal thalamus and amygdala-hippocampal complex volumes within a population at high risk of schizophrenia.
Magnetic resonance imaging scans were obtained from individuals at high genetic risk of schizophrenia at the point of entry to the Edinburgh High-Risk Study (EHRS) and approximately 2 years later. Differential thalamic and amygdala-hippocampal complex volume change in high-risk individuals exposed (n = 25) and not exposed (n = 32) to cannabis in the intervening period was investigated using repeated-measures analysis of variance.
Cannabis exposure was associated with bilateral thalamic volume loss. This effect was significant on the left (F = 4.47, P = 0.04) and highly significant on the right (F=7.66, P=0.008). These results remained significant when individuals using other illicit drugs were removed from the analysis.
These are the first longitudinal data to demonstrate an association between thalamic volume loss and exposure to cannabis in currently unaffected people at familial high risk of developing schizophrenia. This observation may be important in understanding the link between cannabis exposure and the subsequent development of schizophrenia.