Publications by authors named "Elizabeth A Heron"

23 Publications

  • Page 1 of 1

Converting single nucleotide variants between genome builds: from cautionary tale to solution.

Brief Bioinform 2021 09;22(5)

Neuropsychiatric Genetics Research Group in the Department of Psychiatry, Trinity College Dublin, Ireland.

Next-generation sequencing studies are dependent on a high-quality reference genome for single nucleotide variant (SNV) calling. Although the two most recent builds of the human genome are widely used, position information is typically not directly comparable between them. Re-alignment gives the most accurate position information, but this procedure is often computationally expensive, and therefore, tools such as liftOver and CrossMap are used to convert data from one build to another. However, the positions of converted SNVs do not always match SNVs derived from aligned data, and in some instances, SNVs are known to change chromosome when converted. This is a significant problem when compiling sequencing resources or comparing results across studies. Here, we describe a novel algorithm to identify positions that are unstable when converting between human genome reference builds. These positions are detected independent of the conversion tools and are determined by the chain files, which provide a mapping of contiguous positions from one build to another. We also provide the list of unstable positions for converting between the two most commonly used builds GRCh37 and GRCh38. Pre-excluding SNVs at these positions, prior to conversion, results in SNVs that are stable to conversion. This simple procedure gives the same final list of stable SNVs as applying the algorithm and subsequently removing variants at unstable positions. This work highlights the care that must be taken when converting SNVs between genome builds and provides a simple method for ensuring higher confidence converted data. Unstable positions and algorithm code, available at https://github.com/cathaloruaidh/genomeBuildConversion.
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http://dx.doi.org/10.1093/bib/bbab069DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8425424PMC
September 2021

Outcome of First-admission Depression Treated in a Specialized Mood Disorders Service.

J Psychiatr Pract 2020 11;26(6):461-471

Objective: Few studies have described the treatment or outcome of depression in specialized mood disorders units (MDUs). Previous studies have focused on cohorts of patients with highly treatment-resistant illness who are likely to have a poor prognosis even with intensive treatment. This study describes the treatment and medium-term outcomes of a cohort of first-admission depressed patients with less treatment-resistant illness treated in a specialized MDU.

Methods: A cohort of 137 consecutive first-admission depressed patients, referred to an MDU over 2 years, were interviewed using standardized schedules and followed up prospectively from admission for ∼18 months to describe baseline characteristics, treatment, outcome, and predictors of outcome. Times to recovery and recurrence were evaluated using survival analyses and predictors of outcome were examined using bivariate and multivariate regression analyses.

Results: On admission, 75% of the 137 patients had depression that had been found to be resistant to pharmacological treatment, and 34% had been chronically depressed (>2 y). Over half of the patients had likely maladaptive personality traits and one third had at least 1 comorbid psychiatric disorder. By discharge, a significantly higher proportion of the patients were being prescribed very high (P<0.01) or high doses (P<0.05) of antidepressants, augmentation therapy (P<0.001), or a combination of antidepressants (P<0.001) or were engaged in individual psychotherapy (P<0.001), compared with baseline. With intensive treatment, 62% of the patients recovered by 6 months and 76% by 12 months, with 83% overall recovering and patients found to be asymptomatic during almost 60% of the follow-up period. However, 48% suffered a recurrence over the course of the follow-up. Chronicity of mood episodes (P<0.01) and the presence of psychiatric comorbidity (P<0.05) predicted recurrence.

Conclusions: This prospective, naturalistic, medium-term study describes better outcomes, in terms of recovery and symptomatology over time, in a cohort of first-admission depressed patients than previous first-admission studies after continuous, intensive treatment, although the proportion of patients who experienced recurrences remained high.
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http://dx.doi.org/10.1097/PRA.0000000000000509DOI Listing
November 2020

Prevalence of N-Methyl-d-Aspartate Receptor antibody (NMDAR-Ab) encephalitis in patients with first episode psychosis and treatment resistant schizophrenia on clozapine, a population based study.

Schizophr Res 2020 08 1;222:455-461. Epub 2020 Jun 1.

Department of Psychiatry, Trinity College Dublin, Ireland; Department of Psychiatry, St James's Hospital, Dublin, Ireland.

Introduction: N-methyl-d-aspartate receptor antibody (NMDAR-Ab) encephalitis consensus criteria has recently been defined. We aimed to examine the prevalence of NMDAR-Ab encephalitis in patients with first episode psychosis (FEP) and treatment resistant schizophrenia (TRS) on clozapine, using clinical investigations, antibody testing and to retrospectively apply diagnostic consensus criteria.

Methods: Adult (18-65 years old) cases of FEP meeting inclusion criteria were recruited over three years and assessed using the Structured Clinical Interview for DSM-IV disorders (SCID). NMDAR-Ab was identified using a live cell-based assay (L-CBA). Seropositive cases were clinically investigated for features of encephalitis including neuro-imaging, EEG and CSF where possible. Serum was retested using immunohistochemistry (IHC) as part of diagnostic criteria guidelines. A cohort of patients with TRS was also recruited.

Results: 112 FEP patients were recruited over 3 years. NMDAR-Ab seroprevalence was 4/112 (3.5%) cases. One case (<1%) was diagnosed with definite NMDAR-Ab encephalitis and treated with immunotherapy. One of the three other seropositive cases met criteria for probable encephalitis. However all three were ultimately diagnosed with mood disorders with psychotic features. None have developed neurological features at three year follow up. 1/100 (1%) of patients with TRS was 100 patients with TRS were recruited. One case (1%) seropositive for NMDAR-Ab but did not meet criteria for encephalitis.

Conclusions: NMDAR-Ab encephalitis as defined by consensus guidelines occured rarely in psychiatric services in this study. Further studies are needed to establish pathogenicity of serum NMDAR-Ab antibodies. Psychiatric services should be aware of the clinical features of encephalitis.
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http://dx.doi.org/10.1016/j.schres.2019.11.023DOI Listing
August 2020

Identifying schizophrenia patients who carry pathogenic genetic copy number variants using standard clinical assessment: retrospective cohort study.

Br J Psychiatry 2020 05;216(5):275-279

Professor, Head of Discipline, Neuropsychiatric Genetics Research Group, Department of Psychiatry, School of Medicine, Trinity College Dublin, Ireland.

Background: Copy number variants (CNVs) play a significant role in disease pathogenesis in a small subset of individuals with schizophrenia (~2.5%). Chromosomal microarray testing is a first-tier genetic test for many neurodevelopmental disorders. Similar testing could be useful in schizophrenia.

Aims: To determine whether clinically identifiable phenotypic features could be used to successfully model schizophrenia-associated (SCZ-associated) CNV carrier status in a large schizophrenia cohort.

Method: Logistic regression and receiver operating characteristic (ROC) curves tested the accuracy of readily identifiable phenotypic features in modelling SCZ-associated CNV status in a discovery data-set of 1215 individuals with psychosis. A replication analysis was undertaken in a second psychosis data-set (n = 479).

Results: In the discovery cohort, specific learning disorder (OR = 8.12; 95% CI 1.16-34.88, P = 0.012), developmental delay (OR = 5.19; 95% CI 1.58-14.76, P = 0.003) and comorbid neurodevelopmental disorder (OR = 5.87; 95% CI 1.28-19.69, P = 0.009) were significant independent variables in modelling positive carrier status for a SCZ-associated CNV, with an area under the ROC (AUROC) of 74.2% (95% CI 61.9-86.4%). A model constructed from the discovery cohort including developmental delay and comorbid neurodevelopmental disorder variables resulted in an AUROC of 83% (95% CI 52.0-100.0%) for the replication cohort.

Conclusions: These findings suggest that careful clinical history taking to document specific neurodevelopmental features may be informative in screening for individuals with schizophrenia who are at higher risk of carrying known SCZ-associated CNVs. Identification of genomic disorders in these individuals is likely to have clinical benefits similar to those demonstrated for other neurodevelopmental disorders.
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http://dx.doi.org/10.1192/bjp.2019.262DOI Listing
May 2020

Gaining Insights into Aggressive Behaviour in Autism Spectrum Disorder Using Latent Profile Analysis.

J Autism Dev Disord 2019 Oct;49(10):4209-4218

Department of Psychiatry & Neuropsychiatric Genetics Research Group, School of Medicine, The Trinity Centre for Health Sciences, Trinity College Dublin, Dublin 8, Ireland.

Aggressive behaviour is a significant issue for individuals with autism spectrum disorder (ASD), yet our understanding is limited compared to aggression in typically developing populations. This study examined behavioural, adaptive and cognitive data provided by the Simons Simplex Collection (N = 2184) to identify behavioural subgroups in children and adolescents with ASD using latent profile analysis. Results showed five subgroups that differed with regards to behavioural severity, IQ and adaptive behaviour. In two profiles with higher aggression, individuals had greater comorbid anxiety symptoms and attentional deficits and also differed in adaptive behaviour and IQ. These results identify potentially important avenues for research in aggressive behaviour in ASD.
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http://dx.doi.org/10.1007/s10803-019-04129-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6751274PMC
October 2019

Evidence of Assortative Mating in Autism Spectrum Disorder.

Biol Psychiatry 2019 08 22;86(4):286-293. Epub 2019 Apr 22.

Neuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity College Dublin, Trinity Centre for Health Sciences, Dublin, Ireland.

Background: Assortative mating is a nonrandom mating system in which individuals with similar genotypes and/or phenotypes mate with one another more frequently than would be expected in a random mating system. Assortative mating has been hypothesized to play a role in autism spectrum disorder (ASD) in an attempt to explain some of the increase in the prevalence of ASD that has recently been observed. ASD is considered to be a heritable neurodevelopmental disorder, but there is limited understanding of its causes. Assortative mating can be explored through both phenotypic and genotypic data, but up until now it has never been investigated through genotypic measures in ASD.

Methods: We investigated genotypically similar mating pairs using genome-wide single nucleotide polymorphism data on trio families (Autism Genome Project data [1590 parents] and Simons Simplex Collection data [1962 parents]). To determine whether or not an excess in genetic similarity was present, we employed kinship coefficients and examined spousal correlation between the principal components in both the Autism Genome Project and Simons Simplex Collection datasets. We also examined assortative mating using phenotype data on the parents to detect any correlation between ASD traits.

Results: We found significant evidence of genetic similarity between the parents of ASD offspring using both methods in the Autism Genome Project dataset. In the Simons Simplex Collection, there was also significant evidence of genetic similarity between the parents when explored through spousal correlation.

Conclusions: This study gives further support to the hypothesis that positive assortative mating plays a role in ASD.
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http://dx.doi.org/10.1016/j.biopsych.2019.04.014DOI Listing
August 2019

A genome-wide investigation into parent-of-origin effects in autism spectrum disorder identifies previously associated genes including SHANK3.

Eur J Hum Genet 2017 02 23;25(2):234-239. Epub 2016 Nov 23.

Neuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity College Dublin, Trinity Centre for Health Sciences, Dublin, Ireland.

Autism spectrum disorder (ASD) is known to be a heritable neurodevelopmental disorder affecting more than 1% of the population but in the majority of ASD cases, the genetic cause has not been identified. Parent-of-origin effects have been highlighted as an important mechanism in the pathology of neurodevelopmental disorders such as Prader-Willi and Angelman syndrome, with individuals with these syndromes often exhibiting ASD symptoms. Consequently, systematic investigation of these effects in ASD is clearly an important line of investigation in elucidating the underlying genetic mechanisms. Using estimation of maternal, imprinting and interaction effects using multinomial modelling (EMIM), we simultaneously investigated imprinting, maternal genetic effects and associations in the Autism Genome Project and Simons Simplex Consortium genome-wide association data sets. To avoid using the overly stringent genome-wide association study significance level, we used a Bayesian threshold that takes into account the sample size, allele frequency and any available prior knowledge. Between the two data sets, we identified a total of 18 imprinting effects and 68 maternal genetic effects that met this Bayesian threshold criteria, but none met the threshold in both data sets. We identified imprinting and maternal genetic effects for regions that have previously shown evidence for parent-of-origin effects in ASD. Together with these findings, we have identified maternal genetic effects not previously identified in ASD at a locus in SHANK3 on chromosome 22 and a locus in WBSCR17 on chromosome 7 (associated with Williams syndrome). Both genes have previously been associated with ASD.
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http://dx.doi.org/10.1038/ejhg.2016.153DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5255953PMC
February 2017

Traumatic Brain Injury, Sleep, and Mental Health: A Longitudinal Study of Air Force Personnel Pre- and Postdeployment to Iraq.

J Head Trauma Rehabil 2017 Jan/Feb;32(1):25-33

Department of Psychiatry and Behavioral Sciences, University of Oklahoma Health Sciences Center, Oklahoma City (Dr Holster); National Center for Veterans Studies and The University of Utah, Salt Lake City (Dr Bryan); U.S. Air Force Security Forces Center and CNI Advantage, Lackland Air Force Base, San Antonio, Texas (Dr Heron); and Neuropsychology Service, Brooke Army Medical Center, Fort Sam Houston, Texas (Dr Seegmiller).

Objective: We investigated the complex relationships between traumatic brain injury (TBI), sleep, and mental health problems longitudinally among US service members (SMs) pre- and postdeployment to Iraq.

Participants: One hundred sixty-eight SMs enrolled in a 4-week Air Force Basic Combat Convoy Course predeployment.

Design: Self-report data were collected at the beginning and end of training and then at 1, 3, 6, and 12 months postdeployment. Regression analyses were implemented, and participants were categorized into 4 groups based on TBI history for further statistical analysis.

Results: Positive TBI history was associated with greater symptoms of insomnia and posttraumatic stress predeployment and persistence of insomnia symptoms, posttraumatic stress, and depression postdeployment. Positive TBI history and posttraumatic stress served as risk factors for head injury in Iraq, and SMs who reported a head injury during deployment also endorsed greater posttraumatic stress postdeployment than those without head injury. SMs with positive TBI history who also reported a new TBI in Iraq endorsed the greatest sleep and mental health problems across the study period.

Conclusions: This study provides valuable information regarding temporal relationships between TBI, sleep, and mental health problems among a combat military population. Findings have important implications from both prevention and clinical perspectives.
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http://dx.doi.org/10.1097/HTR.0000000000000237DOI Listing
February 2018

Traumatic Brain Injury, Sleep, and Mental Health: A Longitudinal Study of Air Force Personnel Pre- and Postdeployment to Iraq.

J Head Trauma Rehabil 2017 Jan/Feb;32(1):25-33

Department of Psychiatry and Behavioral Sciences, University of Oklahoma Health Sciences Center, Oklahoma City (Dr Holster); National Center for Veterans Studies and The University of Utah, Salt Lake City (Dr Bryan); U.S. Air Force Security Forces Center and CNI Advantage, Lackland Air Force Base, San Antonio, Texas (Dr Heron); and Neuropsychology Service, Brooke Army Medical Center, Fort Sam Houston, Texas (Dr Seegmiller).

Objective: We investigated the complex relationships between traumatic brain injury (TBI), sleep, and mental health problems longitudinally among US service members (SMs) pre- and postdeployment to Iraq.

Participants: One hundred sixty-eight SMs enrolled in a 4-week Air Force Basic Combat Convoy Course predeployment.

Design: Self-report data were collected at the beginning and end of training and then at 1, 3, 6, and 12 months postdeployment. Regression analyses were implemented, and participants were categorized into 4 groups based on TBI history for further statistical analysis.

Results: Positive TBI history was associated with greater symptoms of insomnia and posttraumatic stress predeployment and persistence of insomnia symptoms, posttraumatic stress, and depression postdeployment. Positive TBI history and posttraumatic stress served as risk factors for head injury in Iraq, and SMs who reported a head injury during deployment also endorsed greater posttraumatic stress postdeployment than those without head injury. SMs with positive TBI history who also reported a new TBI in Iraq endorsed the greatest sleep and mental health problems across the study period.

Conclusions: This study provides valuable information regarding temporal relationships between TBI, sleep, and mental health problems among a combat military population. Findings have important implications from both prevention and clinical perspectives.
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http://dx.doi.org/10.1097/HTR.0000000000000237DOI Listing
February 2018

Traumatic Brain Injury, Sleep, and Mental Health: A Longitudinal Study of Air Force Personnel Pre- and Postdeployment to Iraq.

J Head Trauma Rehabil 2017 Jan/Feb;32(1):25-33

Department of Psychiatry and Behavioral Sciences, University of Oklahoma Health Sciences Center, Oklahoma City (Dr Holster); National Center for Veterans Studies and The University of Utah, Salt Lake City (Dr Bryan); U.S. Air Force Security Forces Center and CNI Advantage, Lackland Air Force Base, San Antonio, Texas (Dr Heron); and Neuropsychology Service, Brooke Army Medical Center, Fort Sam Houston, Texas (Dr Seegmiller).

Objective: We investigated the complex relationships between traumatic brain injury (TBI), sleep, and mental health problems longitudinally among US service members (SMs) pre- and postdeployment to Iraq.

Participants: One hundred sixty-eight SMs enrolled in a 4-week Air Force Basic Combat Convoy Course predeployment.

Design: Self-report data were collected at the beginning and end of training and then at 1, 3, 6, and 12 months postdeployment. Regression analyses were implemented, and participants were categorized into 4 groups based on TBI history for further statistical analysis.

Results: Positive TBI history was associated with greater symptoms of insomnia and posttraumatic stress predeployment and persistence of insomnia symptoms, posttraumatic stress, and depression postdeployment. Positive TBI history and posttraumatic stress served as risk factors for head injury in Iraq, and SMs who reported a head injury during deployment also endorsed greater posttraumatic stress postdeployment than those without head injury. SMs with positive TBI history who also reported a new TBI in Iraq endorsed the greatest sleep and mental health problems across the study period.

Conclusions: This study provides valuable information regarding temporal relationships between TBI, sleep, and mental health problems among a combat military population. Findings have important implications from both prevention and clinical perspectives.
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http://dx.doi.org/10.1097/HTR.0000000000000237DOI Listing
February 2018

The phenotypic manifestations of rare CNVs in schizophrenia.

Schizophr Res 2014 Sep 4;158(1-3):255-60. Epub 2014 Jul 4.

Department of Psychiatry & Neuropsychiatric Genetics Research Group, Institute of Molecular Medicine, Trinity College Dublin, Dublin 2, Ireland.

There is compelling evidence for the role of copy number variants (CNVs) in schizophrenia susceptibility, and it has been estimated that up to 2-3% of schizophrenia cases may carry rare CNVs. Despite evidence that these events are associated with an increased risk across categorical neurodevelopmental disorders, there is limited understanding of the impact of CNVs on the core features of disorders like schizophrenia. Our objective was to evaluate associations between rare CNVs in differentially brain expressed (BE) genes and the core features and clinical correlates of schizophrenia. The sample included 386 cases of Irish ancestry with a diagnosis of schizophrenia, at least one rare CNV impacting any gene, and a core set of phenotypic measures. Statistically significant associations between deletions in differentially BE genes were found for family history of mental illness (decreased prevalence of all CNVs and deletions, unadjusted and adjusted) and for paternal age (increase in deletions only, unadjusted, among those with later ages at birth of patient). The strong effect of a lack of a family history on BE genes suggests that CNVs may comprise one pathway to schizophrenia, whereas a positive family history could index other genetic mechanisms that increase schizophrenia vulnerability. To our knowledge, this is the first investigation of the association between genome-wide CNVs and risk factors and sub-phenotypic features of schizophrenia beyond cognitive function.
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http://dx.doi.org/10.1016/j.schres.2014.06.016DOI Listing
September 2014

Review of statistical methodologies for the detection of parent-of-origin effects in family trio genome-wide association data with binary disease traits.

Brief Bioinform 2015 May 5;16(3):429-48. Epub 2014 Jun 5.

The detection of parent-of-origin effects aims to identify whether the functionality of alleles, and in turn associated phenotypic traits, depends on the parental origin of the alleles. Different parent-of-origin effects have been identified through a variety of mechanisms and a number of statistical methodologies for their detection have been proposed, in particular for genome-wide association studies (GWAS). GWAS have had limited success in explaining the heritability of many complex disorders and traits, but successful identification of parent-of-origin effects using trio (mother, father and offspring) GWAS may help shed light on this missing heritability. However, it is important to choose the most appropriate parent-of-origin test or methodology, given knowledge of the phenotype, amount of available data and the type of parent-of-origin effect(s) being considered. This review brings together the parent-of-origin detection methodologies available, comparing them in terms of power and type I error for a number of different simulated data scenarios, and finally offering guidance as to the most appropriate choice for the different scenarios.
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http://dx.doi.org/10.1093/bib/bbu017DOI Listing
May 2015

No evidence that runs of homozygosity are associated with schizophrenia in an Irish genome-wide association dataset.

Schizophr Res 2014 Apr 20;154(1-3):79-82. Epub 2014 Feb 20.

Department of Psychiatry & Neuropsychiatric Genetics Research Group, School of Medicine, The Trinity Centre for Health Sciences, St. James's Hospital, Dublin 8, Ireland. Electronic address:

Runs of homozygosity (ROH), regions of the genome containing many consecutive homozygous SNPs, may represent two copies of a haplotype inherited from a common ancestor. A rare variant on this haplotype could thus be present in a homozygous and potentially recessive state. To detect rare risk variants for schizophrenia, we performed an ROH analysis in a homogeneous Irish genome wide association study (GWAS) dataset consisting of 1606 cases and 1794 controls. There was no genome-wide excess of ROH in cases compared to controls (p=0.7986). No consensus ROH at individual loci showed association with schizophrenia after genome-wide correction.
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http://dx.doi.org/10.1016/j.schres.2014.01.038DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4034753PMC
April 2014

Military mental health: the role of daily hassles while deployed.

J Nerv Ment Dis 2013 Dec;201(12):1035-9

*342d Training Squadron, Lackland Air Force Base; †National Center for Veterans Studies, The University of Utah, Salt Lake City; and ‡Battelle Scientific Services, Lackland Air Force Base, San Antonio, TX.

This study sought to identify factors contributing to symptoms of depression and posttraumatic stress disorder (PTSD) in recently deployed combat veterans. A sample of 168 active duty military personnel completed measures of combat exposure, deployment-related daily hassles, depression symptoms, and PTSD symptoms at six time points across their deployment: predeployment and 1, 3, 6, and 12 months postdeployment. Mixed-effects linear modeling with repeated measures was used to identify factors associated with depression and PTSD severity over time. Postdeployment depression severity did not change over time, but PTSD severity decreased slightly over time after returning home. Postdeployment depression severity was predicted by past (but not recent) combat exposure, daily hassles, and concurrent PTSD symptoms. Postdeployment PTSD severity was predicted by past and recent combat exposure, concurrent depression symptoms, and male sex. Depression severity mediated the relationship between daily hassles and postdeployment PTSD severity.
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http://dx.doi.org/10.1097/NMD.0000000000000058DOI Listing
December 2013

Mauling of the "Celtic Tiger": clinical characteristics and outcome of first-episode depression secondary to the economic recession in Ireland.

J Affect Disord 2013 Nov 12;151(2):455-460. Epub 2013 Aug 12.

Department of Psychiatry, Trinity College Dublin, St. Patrick's University Hospital, Dublin 8, Ireland. Electronic address:

Background: There is a dearth of studies describing clinical characteristics and outcome of patients who present with mood disorders related to economic recession.

Aims: To describe a cohort of patients admitted with first-episode depression related to the Irish economic recession and compare this cohort with all other first-episode depressives admitted during the same time period (2009-2010).

Methods: A cohort of 137 patients admitted with first-episode depression to an independent university teaching hospital was prospectively identified and followed up from admission over 2 years (mean follow-up 430 days, s.d. 176 days). The cohort was divided into "Celtic Tiger" (patients with first-episode depression secondary to the economic recession) and non-Celtic Tiger control patients (other first-episode depressed patients). Both groups were compared in terms of clinical characteristics at baseline and outcome over follow-up.

Results: The number of admissions due to first depressive episodes were higher in recession years 2009/10 than in pre-recession years 2008/9. Celtic Tiger patients were predominantly male and more severely depressed with more marked suicidal ideation (χ(2), p<0.001) than control patients. They were more likely to recover (χ(2), p=0.013), less likely to recur (χ(2), p<0.001) and had faster time to recovery (log rank, p<0.001) and slower time to full recurrence (log rank, p=0.001). The Celtic Tiger patients spent more time asymptomatic and less time at full and subthreshold depression levels over follow-up.

Limitations: Study setting of centre specializing in affective disorders treatment, retrospective nature of follow-up after initial prospective interview and lack of patient follow-up interview.

Conclusion: The study describes a subgroup of patients with severe depression associated with economic recession with likely high suicide risk but very favourable outcome.
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http://dx.doi.org/10.1016/j.jad.2013.06.024DOI Listing
November 2013

Individual common variants exert weak effects on the risk for autism spectrum disorders.

Hum Mol Genet 2012 Nov 26;21(21):4781-92. Epub 2012 Jul 26.

Autism Genetics Group, Department of Psychiatry, School of Medicine, Trinity College, Dublin 8, Ireland.

While it is apparent that rare variation can play an important role in the genetic architecture of autism spectrum disorders (ASDs), the contribution of common variation to the risk of developing ASD is less clear. To produce a more comprehensive picture, we report Stage 2 of the Autism Genome Project genome-wide association study, adding 1301 ASD families and bringing the total to 2705 families analysed (Stages 1 and 2). In addition to evaluating the association of individual single nucleotide polymorphisms (SNPs), we also sought evidence that common variants, en masse, might affect the risk. Despite genotyping over a million SNPs covering the genome, no single SNP shows significant association with ASD or selected phenotypes at a genome-wide level. The SNP that achieves the smallest P-value from secondary analyses is rs1718101. It falls in CNTNAP2, a gene previously implicated in susceptibility for ASD. This SNP also shows modest association with age of word/phrase acquisition in ASD subjects, of interest because features of language development are also associated with other variation in CNTNAP2. In contrast, allele scores derived from the transmission of common alleles to Stage 1 cases significantly predict case status in the independent Stage 2 sample. Despite being significant, the variance explained by these allele scores was small (Vm< 1%). Based on results from individual SNPs and their en masse effect on risk, as inferred from the allele score results, it is reasonable to conclude that common variants affect the risk for ASD but their individual effects are modest.
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http://dx.doi.org/10.1093/hmg/dds301DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3471395PMC
November 2012

Genetic classification of populations using supervised learning.

PLoS One 2011 May 12;6(5):e14802. Epub 2011 May 12.

Astrophysics Group, Cavendish Laboratory, Cambridge, United Kingdom.

There are many instances in genetics in which we wish to determine whether two candidate populations are distinguishable on the basis of their genetic structure. Examples include populations which are geographically separated, case-control studies and quality control (when participants in a study have been genotyped at different laboratories). This latter application is of particular importance in the era of large scale genome wide association studies, when collections of individuals genotyped at different locations are being merged to provide increased power. The traditional method for detecting structure within a population is some form of exploratory technique such as principal components analysis. Such methods, which do not utilise our prior knowledge of the membership of the candidate populations. are termed unsupervised. Supervised methods, on the other hand are able to utilise this prior knowledge when it is available.In this paper we demonstrate that in such cases modern supervised approaches are a more appropriate tool for detecting genetic differences between populations. We apply two such methods, (neural networks and support vector machines) to the classification of three populations (two from Scotland and one from Bulgaria). The sensitivity exhibited by both these methods is considerably higher than that attained by principal components analysis and in fact comfortably exceeds a recently conjectured theoretical limit on the sensitivity of unsupervised methods. In particular, our methods can distinguish between the two Scottish populations, where principal components analysis cannot. We suggest, on the basis of our results that a supervised learning approach should be the method of choice when classifying individuals into pre-defined populations, particularly in quality control for large scale genome wide association studies.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0014802PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3093382PMC
May 2011

Exploration of empirical Bayes hierarchical modeling for the analysis of genome-wide association study data.

Biostatistics 2011 Jul 20;12(3):445-61. Epub 2011 Jan 20.

Neuropsychiatric Genetics Research Group and Department of Psychiatry, Trinity College Dublin, Trinity Centre for Health Sciences, James's Street, Dublin 8, Ireland.

In the analysis of genome-wide association (GWA) data, the aim is to detect statistical associations between single nucleotide polymorphisms (SNPs) and the disease or trait of interest. These SNPs, or the particular regions of the genome they implicate, are then considered for further study. We demonstrate through a comprehensive simulation study that the inclusion of additional, biologically relevant information through a 2-level empirical Bayes hierachical model framework offers a more robust method of detecting associated SNPs. The empirical Bayes approach is an objective means of analyzing the data without the need for the setting of subjective parameter estimates. This framework gives more stable estimates of effects through a reduction of the variability in the usual effect estimates. We also demonstrate the consequences of including additional information that is not informative and examine power and false-positive rates. We apply the methodology to a number of genome-wide association (GWA) data sets with the inclusion of additional biological information. Our results agree with previous findings and in the case of one data set (Crohn's disease) suggest an additional region of interest.
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http://dx.doi.org/10.1093/biostatistics/kxq072DOI Listing
July 2011

A genome-wide scan for common alleles affecting risk for autism.

Hum Mol Genet 2010 Oct 27;19(20):4072-82. Epub 2010 Jul 27.

Department of Psychiatry, School of Medicine, Trinity College, Dublin 8, Ireland.

Although autism spectrum disorders (ASDs) have a substantial genetic basis, most of the known genetic risk has been traced to rare variants, principally copy number variants (CNVs). To identify common risk variation, the Autism Genome Project (AGP) Consortium genotyped 1558 rigorously defined ASD families for 1 million single-nucleotide polymorphisms (SNPs) and analyzed these SNP genotypes for association with ASD. In one of four primary association analyses, the association signal for marker rs4141463, located within MACROD2, crossed the genome-wide association significance threshold of P < 5 × 10(-8). When a smaller replication sample was analyzed, the risk allele at rs4141463 was again over-transmitted; yet, consistent with the winner's curse, its effect size in the replication sample was much smaller; and, for the combined samples, the association signal barely fell below the P < 5 × 10(-8) threshold. Exploratory analyses of phenotypic subtypes yielded no significant associations after correction for multiple testing. They did, however, yield strong signals within several genes, KIAA0564, PLD5, POU6F2, ST8SIA2 and TAF1C.
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http://dx.doi.org/10.1093/hmg/ddq307DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2947401PMC
October 2010

Functional impact of global rare copy number variation in autism spectrum disorders.

Nature 2010 Jul 9;466(7304):368-72. Epub 2010 Jun 9.

The Centre for Applied Genomics and Program in Genetics and Genomic Biology, The Hospital for Sick Children, Toronto, Ontario M5G 1L7, Canada.

The autism spectrum disorders (ASDs) are a group of conditions characterized by impairments in reciprocal social interaction and communication, and the presence of restricted and repetitive behaviours. Individuals with an ASD vary greatly in cognitive development, which can range from above average to intellectual disability. Although ASDs are known to be highly heritable ( approximately 90%), the underlying genetic determinants are still largely unknown. Here we analysed the genome-wide characteristics of rare (<1% frequency) copy number variation in ASD using dense genotyping arrays. When comparing 996 ASD individuals of European ancestry to 1,287 matched controls, cases were found to carry a higher global burden of rare, genic copy number variants (CNVs) (1.19 fold, P = 0.012), especially so for loci previously implicated in either ASD and/or intellectual disability (1.69 fold, P = 3.4 x 10(-4)). Among the CNVs there were numerous de novo and inherited events, sometimes in combination in a given family, implicating many novel ASD genes such as SHANK2, SYNGAP1, DLGAP2 and the X-linked DDX53-PTCHD1 locus. We also discovered an enrichment of CNVs disrupting functional gene sets involved in cellular proliferation, projection and motility, and GTPase/Ras signalling. Our results reveal many new genetic and functional targets in ASD that may lead to final connected pathways.
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http://dx.doi.org/10.1038/nature09146DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3021798PMC
July 2010

The SNP ratio test: pathway analysis of genome-wide association datasets.

Bioinformatics 2009 Oct 20;25(20):2762-3. Epub 2009 Jul 20.

Neuropsychiatric Genetics Research Group, Department of Psychiatry, Trinity College Dublin, Ireland.

Unlabelled: We present a tool that assesses the enrichment of significant associations from genome-wide association studies (GWAS) in a pathway context. The SNP ratio test (SRT) compares the proportion of significant to all SNPs within genes that are part of a pathway and computes an empirical P-value based on comparisons to ratios in datasets where the assignment of case/control status has been randomized. We applied the SRT to a Parkinson's disease GWAS dataset, using the KEGG database, revealing significance for Parkinson's disease and related pathways.

Availability: https://sourceforge.net/projects/snpratiotest/
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http://dx.doi.org/10.1093/bioinformatics/btp448DOI Listing
October 2009

Reconstruction of transcriptional dynamics from gene reporter data using differential equations.

Bioinformatics 2008 Dec 30;24(24):2901-7. Epub 2008 Oct 30.

Department of Statistics, University of Warwick, Coventry CV47AL, UK.

Motivation: Promoter-driven reporter genes, notably luciferase and green fluorescent protein, provide a tool for the generation of a vast array of time-course data sets from living cells and organisms. The aim of this study is to introduce a modeling framework based on stochastic differential equations (SDEs) and ordinary differential equations (ODEs) that addresses the problem of reconstructing transcription time-course profiles and associated degradation rates. The dynamical model is embedded into a Bayesian framework and inference is performed using Markov chain Monte Carlo algorithms.

Results: We present three case studies where the methodology is used to reconstruct unobserved transcription profiles and to estimate associated degradation rates. We discuss advantages and limits of fitting either SDEs ODEs and address the problem of parameter identifiability when model variables are unobserved. We also suggest functional forms, such as on/off switches and stimulus response functions to model transcriptional dynamics and present results of fitting these to experimental data.
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http://dx.doi.org/10.1093/bioinformatics/btn562DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2639297PMC
December 2008

Bayesian inference for dynamic transcriptional regulation; the Hes1 system as a case study.

Bioinformatics 2007 Oct 28;23(19):2596-603. Epub 2007 Jul 28.

Warwick Systems Biology Centre, University of Warwick, Coventry CV4 7AL, UK.

Motivation: In this study, we address the problem of estimating the parameters of regulatory networks and provide the first application of Markov chain Monte Carlo (MCMC) methods to experimental data. As a case study, we consider a stochastic model of the Hes1 system expressed in terms of stochastic differential equations (SDEs) to which rigorous likelihood methods of inference can be applied. When fitting continuous-time stochastic models to discretely observed time series the lengths of the sampling intervals are important, and much of our study addresses the problem when the data are sparse.

Results: We estimate the parameters of an autoregulatory network providing results both for simulated and real experimental data from the Hes1 system. We develop an estimation algorithm using MCMC techniques which are flexible enough to allow for the imputation of latent data on a finer time scale and the presence of prior information about parameters which may be informed from other experiments as well as additional measurement error.
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http://dx.doi.org/10.1093/bioinformatics/btm367DOI Listing
October 2007
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