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1.
Transl Psychiatry ; 9(1): 187, 2019 Aug 05.
Artigo em Inglês | MEDLINE | ID: mdl-31383853

RESUMO

The identification of generalizable treatment response classes (TRC[s]) in major depressive disorder (MDD) would facilitate comparisons across studies and the development of treatment prediction algorithms. Here, we investigated whether such stable TRCs can be identified and predicted by clinical baseline items. We analyzed data from an observational MDD cohort (Munich Antidepressant Response Signature [MARS] study, N = 1017), treated individually by psychopharmacological and psychotherapeutic means, and a multicenter, partially randomized clinical/pharmacogenomic study (Genome-based Therapeutic Drugs for Depression [GENDEP], N = 809). Symptoms were evaluated up to week 16 (or discharge) in MARS and week 12 in GENDEP. Clustering was performed on 809 MARS patients (discovery sample) using a mixed model with the integrated completed likelihood criterion for the assessment of cluster stability, and validated through a distinct MARS validation sample and GENDEP. A random forest algorithm was used to identify prediction patterns based on 50 clinical baseline items. From the clustering of the MARS discovery sample, seven TRCs emerged ranging from fast and complete response (average 4.9 weeks until discharge, 94% remitted patients) to slow and incomplete response (10% remitted patients at week 16). These proved stable representations of treatment response dynamics in both the MARS and the GENDEP validation sample. TRCs were strongly associated with established response markers, particularly the rate of remitted patients at discharge. TRCs were predictable from clinical items, particularly personality items, life events, episode duration, and specific psychopathological features. Prediction accuracy improved significantly when cluster-derived slopes were modelled instead of individual slopes. In conclusion, model-based clustering identified distinct and clinically meaningful treatment response classes in MDD that proved robust with regard to capturing response profiles of differently designed studies. Response classes were predictable from clinical baseline characteristics. Conceptually, model-based clustering is translatable to any outcome measure and could advance the large-scale integration of studies on treatment efficacy or the neurobiology of treatment response.

2.
Artigo em Inglês | MEDLINE | ID: mdl-31202982

RESUMO

BACKGROUND & AIMS: Relatives of individuals with Crohn's disease (CD) carry CD-associated genetic variants and are often exposed to environmental factors that increase their risk for this disease. We aimed to estimate the utility of genotype, smoking status, family history, and other biomarkers can be used to calculate risk in asymptomatic first-degree relatives of patients with CD. METHODS: We recruited 480 healthy first-degree relatives (full siblings, offspring or parents) of patients with CD through the Guy's and St Thomas' NHS Foundation Trust and from members of Crohn's and Colitis, United Kingdom. DNA samples were genotyped using the Immunochip. We calculated a risk score for 454 participants, based on 72 genetic variants associated with CD, family history, and smoking history. Participants were assigned to highest and lowest risk score quartiles. We assessed pre-symptomatic inflammation by capsule endoscopy and measured 22 markers of inflammation in stool and serum samples (reference standard). Two machine-learning classifiers (elastic net and random forest) were used to assess the ability of the risk factors and biomarkers to identify participants with small intestinal inflammation in the same dataset. RESULTS: The machine-learning classifiers identified participants with pre-symptomatic intestinal inflammation: elastic net (area under the curve, 0.80; 95% CI, 0.62-0.98) and random forest (area under the curve, 0.87; 95% CI, 0.75-1.00). The elastic net method identified 3 variables that can be used to calculate odds for intestinal inflammation: combined family history of CD (odds ratio, 1.31), genetic risk score (odds ratio, 1.14), and fecal level of calprotectin (odds ratio, 1.04). These same 3 variables were among the 5 factors associated with intestinal inflammation in the random forest model. CONCLUSION: Using machine learning classifiers, we found that genetic variants associated with CD, family history, and fecal level of calprotectin together identify individuals with pre-symptomatic intestinal inflammation who are therefore at risk for CD. A tool for detecting people at risk for CD before they develop symptoms would help identify the individuals most likely to benefit from early intervention.

3.
JAMA Dermatol ; 2019 Jun 05.
Artigo em Inglês | MEDLINE | ID: mdl-31166567

RESUMO

Importance: Advanced liver fibrosis is a precursor to cirrhosis, a leading cause of mortality. People with severe psoriasis are at risk for liver disease, but our understanding of advanced fibrosis in individuals with psoriasis is limited. Objectives: To describe the prevalence of and evaluate the clinical factors associated with advanced liver fibrosis in people with severe psoriasis. Design, Setting, and Participants: The Co-morbidities in Severe Psoriasis study, a prospective observational cohort study in a large center serving London and Southeast England, was conducted from October 18, 2012, to April 2, 2015; 400 adults with severe psoriasis (Psoriasis Area Severity Index score, ≥10) were recruited from outpatient clinics. Statistical analysis was conducted from October 2, 2016, to March 3, 2017. Main Outcomes and Measures: The primary outcome was a diagnosis of advanced liver fibrosis determined by transient elastography, a noninvasive criterion standard test. Clinical factors evaluated included psoriasis-specific and metabolic indices, alcohol use, and methotrexate exposure. Results: Of 400 patients recruited (108 women and 289 men; mean [SD] age, 49.5 [13] years), 333 had a successful transient elastography scan and were included in final analysis. Forty-seven patients (14.1%; 95% CI, 10.4%-17.9%) had advanced liver fibrosis as diagnosed by transient elastography. The clinical factors that produced the best-fit model for advanced fibrosis were central obesity (waist circumference), insulin resistance, aspartate aminotransferase level, platelet count, psoriasis disease severity, and reduced alcohol use (R2 = 0.54). Conclusions and Relevance: Findings from this study suggest that advanced fibrosis is common in severe psoriasis. Abdominal obesity (by waist circumference) and insulin resistance were associated with the presence of advanced fibrosis. Longitudinal work to characterize the hepatic sequelae of central obesity, insulin resistance, and inflammation as well as the influence of systemic drugs (methotrexate and biologics) will inform future personalized therapeutic decision-making. Trial Registration: ClinicalTrials.gov identifier: NCT02174367.

4.
PLoS One ; 14(5): e0214311, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31150407

RESUMO

INTRODUCTION: The UK Biobank (UKB) is a resource that includes detailed health-related data on about 500,000 individuals and is available to the research community. However, several obstacles limit immediate analysis of the data: data files vary in format, may be very large, and have numerical codes for column names. RESULTS: ukbtools removes all the upfront data wrangling required to get a single dataset for statistical analysis. All associated data files are merged into a single dataset with descriptive column names. The package also provides tools to assist in quality control by exploring the primary demographics of subsets of participants; query of disease diagnoses for one or more individuals, and estimating disease frequency relative to a reference variable; and to retrieve genetic metadata. CONCLUSION: Having a dataset with meaningful variable names, a set of UKB-specific exploratory data analysis tools, disease query functions, and a set of helper functions to explore and write genetic metadata to file, will rapidly enable UKB users to undertake their research.

5.
Psychoneuroendocrinology ; 106: 284-292, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31039525

RESUMO

Altered reproductive hormone levels have been associated with the pathophysiology of depressive disorders and this risk may be imparted by their modulatory effect upon hippocampal structure and function. Currently it is unclear whether altered levels of reproductive hormones are causally associated with hippocampal volume reductions and the risk of depressive disorders. Here, we utilize genome-wide association study (GWAS) summary statistics from a GWAS focusing on reproductive hormones, consisting of 2913 individuals. Using this data, we generated polygenic risk scores (PRS) for estradiol, progesterone, prolactin and testosterone in the European RADIANT cohort consisting of 176 postpartum depression (PPD) cases (100% female, mean age: 41.6 years old), 2772 major depressive disorder (MDD) cases (68.6% female, mean age: 46.9 years old) and 1588 control participants (62.5% female, mean age: 42.4 years old), for which there was also a neuroimaging subset of 111 individuals (60.4% female, mean age: 50.0 years old). Only the best-fit PRS for estradiol showed a significant negative association with hippocampal volume, as well as many of its individual subfields; including the molecular layer and granule cell layer of the dentate gyrus, subiculum, CA1, CA2/3 and CA4 regions. Interestingly, several of these subfields are implicated in adult hippocampal neurogenesis. When we tested the same estradiol PRS for association with case-control status for PPD or MDD there was no significant relationship observed. Here, we provide evidence that genetic risk for higher plasma estradiol is negatively associated with hippocampal volume, but this does not translate into an increased risk of MDD or PPD. This work suggests that the relationship between reproductive hormones, the hippocampus, and depression is complex, and that there may not be a clear-cut pathway for etiology or risk moderation.

6.
Mov Disord ; 34(7): 1049-1059, 2019 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-31059154

RESUMO

BACKGROUND: Progressive supranuclear palsy is a neurodegenerative tauopathy manifesting clinically as a progressive akinetic-rigid syndrome. In this study, we sought to identify genetic variants influencing PSP susceptibility through a genome-wide association analysis of a cohort of well-characterized patients who had participated in the Neuroprotection and Natural History in Parkinson Plus Syndromes and Blood Brain Barrier in Parkinson Plus Syndromes studies. METHODS: We genotyped single-nucleotide polymorphisms in 283 PSP cases from the United Kingdom, Germany, and France and compared these with genotypes from 4472 controls. Copy number variants were identified from genotyping data. RESULTS: We observed associations on chromosome 17 within or close to the MAPT gene and explored the genetic architecture at this locus. We confirmed the previously reported association of rs1768208 in the MOBP gene (P = 3.29 × 10-13 ) and rs1411478 in STX6 (P = 3.45 × 10-10 ). The population-attributable risk from the MAPT, MOBP, and STX6 single-nucleotide polymorphisms was found to be 0.37, 0.26, and 0.08, respectively. In addition, we found 2 instances of copy number variants spanning the MAPT gene in patients with PSP. These copy number variants include tau but few other genes within the chromosome 17 haplotype region, providing additional support for the direct pathogenicity of MAPT in PSP. CONCLUSIONS: Clinicians should also be aware of MAPT duplication as a possible genetic cause of PSP, especially in patients presenting with young age at onset. © 2019 International Parkinson and Movement Disorder Society.

7.
Psychol Med ; 49(7): 1218-1226, 2019 May.
Artigo em Inglês | MEDLINE | ID: mdl-30929657

RESUMO

BACKGROUND: Despite established clinical associations among major depression (MD), alcohol dependence (AD), and alcohol consumption (AC), the nature of the causal relationship between them is not completely understood. We leveraged genome-wide data from the Psychiatric Genomics Consortium (PGC) and UK Biobank to test for the presence of shared genetic mechanisms and causal relationships among MD, AD, and AC. METHODS: Linkage disequilibrium score regression and Mendelian randomization (MR) were performed using genome-wide data from the PGC (MD: 135 458 cases and 344 901 controls; AD: 10 206 cases and 28 480 controls) and UK Biobank (AC-frequency: 438 308 individuals; AC-quantity: 307 098 individuals). RESULTS: Positive genetic correlation was observed between MD and AD (rgMD-AD = + 0.47, P = 6.6 × 10-10). AC-quantity showed positive genetic correlation with both AD (rgAD-AC quantity = + 0.75, P = 1.8 × 10-14) and MD (rgMD-AC quantity = + 0.14, P = 2.9 × 10-7), while there was negative correlation of AC-frequency with MD (rgMD-AC frequency = -0.17, P = 1.5 × 10-10) and a non-significant result with AD. MR analyses confirmed the presence of pleiotropy among these four traits. However, the MD-AD results reflect a mediated-pleiotropy mechanism (i.e. causal relationship) with an effect of MD on AD (beta = 0.28, P = 1.29 × 10-6). There was no evidence for reverse causation. CONCLUSION: This study supports a causal role for genetic liability of MD on AD based on genetic datasets including thousands of individuals. Understanding mechanisms underlying MD-AD comorbidity addresses important public health concerns and has the potential to facilitate prevention and intervention efforts.

8.
Neuron ; 102(1): 91-103, 2019 Apr 03.
Artigo em Inglês | MEDLINE | ID: mdl-30946830

RESUMO

There have been several recent studies addressing the genetic architecture of depression. This review serves to take stock of what is known now about the genetics of depression, how it has increased our knowledge and understanding of its mechanisms, and how the information and knowledge can be leveraged to improve the care of people affected. We identify four priorities for how the field of MD genetics research may move forward in future years, namely by increasing the sample sizes available for genome-wide association studies (GWASs), greater inclusion of diverse ancestries and low-income countries, the closer integration of psychiatric genetics with electronic medical records, and the development of the neuroscience toolkit for polygenic disorders.

9.
Biol Psychiatry ; 85(12): 1065-1073, 2019 Jun 15.
Artigo em Inglês | MEDLINE | ID: mdl-31003785

RESUMO

BACKGROUND: Major depressive disorder (MDD) is moderately heritable, with a high prevalence and a presumed high heterogeneity. Copy number variants (CNVs) could contribute to the heritable component of risk, but the two previous genome-wide association studies of rare CNVs did not report significant findings. METHODS: In this meta-analysis of four cohorts (5780 patients and 6626 control subjects), we analyzed the association of MDD to 1) genome-wide burden of rare deletions and duplications, partitioned by length (<100 kb or >100 kb) and other characteristics, and 2) individual rare exonic CNVs and CNV regions. RESULTS: Patients with MDD carried significantly more short deletions than control subjects (p = .0059) but not long deletions or short or long duplications. The confidence interval for long deletions overlapped with that for short deletions, but long deletions were 70% less frequent genome-wide, reducing the power to detect increased burden. The increased burden of short deletions was primarily in intergenic regions. Short deletions in cases were also modestly enriched for high-confidence enhancer regions. No individual CNV achieved thresholds for suggestive or significant association after genome-wide correction. p values < .01 were observed for 15q11.2 duplications (TUBGCP5, CYFIP1, NIPA1, and NIPA2), deletions in or near PRKN or MSR1, and exonic duplications of ATG5. CONCLUSIONS: The increased burden of short deletions in patients with MDD suggests that rare CNVs increase the risk of MDD by disrupting regulatory regions. Results for longer deletions were less clear, but no large effects were observed for long multigenic CNVs (as seen in schizophrenia and autism). Further studies with larger sample sizes are warranted.

10.
Lancet Psychiatry ; 6(5): 427-436, 2019 May.
Artigo em Inglês | MEDLINE | ID: mdl-30902669

RESUMO

BACKGROUND: Cannabis use is associated with increased risk of later psychotic disorder but whether it affects incidence of the disorder remains unclear. We aimed to identify patterns of cannabis use with the strongest effect on odds of psychotic disorder across Europe and explore whether differences in such patterns contribute to variations in the incidence rates of psychotic disorder. METHODS: We included patients aged 18-64 years who presented to psychiatric services in 11 sites across Europe and Brazil with first-episode psychosis and recruited controls representative of the local populations. We applied adjusted logistic regression models to the data to estimate which patterns of cannabis use carried the highest odds for psychotic disorder. Using Europe-wide and national data on the expected concentration of Δ9-tetrahydrocannabinol (THC) in the different types of cannabis available across the sites, we divided the types of cannabis used by participants into two categories: low potency (THC <10%) and high potency (THC ≥10%). Assuming causality, we calculated the population attributable fractions (PAFs) for the patterns of cannabis use associated with the highest odds of psychosis and the correlation between such patterns and the incidence rates for psychotic disorder across the study sites. FINDINGS: Between May 1, 2010, and April 1, 2015, we obtained data from 901 patients with first-episode psychosis across 11 sites and 1237 population controls from those same sites. Daily cannabis use was associated with increased odds of psychotic disorder compared with never users (adjusted odds ratio [OR] 3·2, 95% CI 2·2-4·1), increasing to nearly five-times increased odds for daily use of high-potency types of cannabis (4·8, 2·5-6·3). The PAFs calculated indicated that if high-potency cannabis were no longer available, 12·2% (95% CI 3·0-16·1) of cases of first-episode psychosis could be prevented across the 11 sites, rising to 30·3% (15·2-40·0) in London and 50·3% (27·4-66·0) in Amsterdam. The adjusted incident rates for psychotic disorder were positively correlated with the prevalence in controls across the 11 sites of use of high-potency cannabis (r = 0·7; p=0·0286) and daily use (r = 0·8; p=0·0109). INTERPRETATION: Differences in frequency of daily cannabis use and in use of high-potency cannabis contributed to the striking variation in the incidence of psychotic disorder across the 11 studied sites. Given the increasing availability of high-potency cannabis, this has important implications for public health. FUNDING SOURCE: Medical Research Council, the European Community's Seventh Framework Program grant, São Paulo Research Foundation, National Institute for Health Research (NIHR) Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust and King's College London and the NIHR BRC at University College London, Wellcome Trust.

11.
Carcinogenesis ; 40(4): 513-520, 2019 Jun 10.
Artigo em Inglês | MEDLINE | ID: mdl-30753320

RESUMO

Oesophageal squamous cell carcinoma (OSCC) has a high incidence in southern Africa and a poor prognosis. Limited information is available on the contribution of genetic variants in susceptibility to OSCC in this region. However, recent genome-wide association studies have identified multiple susceptibility loci in Asian and European populations. In this study, we investigated genetic variants from seven OSCC risk loci identified in non-African populations for association with OSCC in the South African Black population. We performed association studies in a total of 1471 cases and 1791 controls from two study sample groups, which included 591 cases and 852 controls from the Western Cape and 880 cases and 939 controls from the Johannesburg region in the Gauteng province. Thereafter, we performed a meta-analysis for 11 variants which had been genotyped in both studies. A single nucleotide polymorphism in the CHEK2 gene, rs1033667, was significantly associated with OSCC [P = 0.002; odds ratio (OR) = 1.176; 95% confidence interval (CI): 1.06-1.30]. However, single nucleotide polymorphisms in the CASP8/ALS2CR12, TMEM173, PLCE1, ALDH2, ATP1B2/TP53 and RUNX1 loci were not associated with the disease (P > 0.05). The lack of association of six of these loci with OSCC in South African populations may reflect different genetic risk factors in non-African and African populations or differences in the genetic architecture of African genomes. The association at CHEK2, a gene with key roles in cell cycle regulation and DNA repair, in an African population provides further support for the contribution of common genetic variants at this locus to the risk of oesophageal cancer.

12.
Am J Med Genet B Neuropsychiatr Genet ; 180(6): 439-447, 2019 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-30708398

RESUMO

Major depressive disorder (MDD) is clinically heterogeneous with prevalence rates twice as high in women as in men. There are many possible sources of heterogeneity in MDD most of which are not measured in a sufficiently comparable way across study samples. Here, we assess genetic heterogeneity based on two fundamental measures, between-cohort and between-sex heterogeneity. First, we used genome-wide association study (GWAS) summary statistics to investigate between-cohort genetic heterogeneity using the 29 research cohorts of the Psychiatric Genomics Consortium (PGC; N cases = 16,823, N controls = 25,632) and found that some of the cohort heterogeneity can be attributed to ascertainment differences (such as recruitment of cases from hospital vs. community sources). Second, we evaluated between-sex genetic heterogeneity using GWAS summary statistics from the PGC, Kaiser Permanente GERA, UK Biobank, and the Danish iPSYCH studies but did not find convincing evidence for genetic differences between the sexes. We conclude that there is no evidence that the heterogeneity between MDD data sets and between sexes reflects genetic heterogeneity. Larger sample sizes with detailed phenotypic records and genomic data remain the key to overcome heterogeneity inherent in assessment of MDD.

13.
Pharmacogenomics J ; 2019 Jan 31.
Artigo em Inglês | MEDLINE | ID: mdl-30700811

RESUMO

Antidepressants demonstrate modest response rates in the treatment of major depressive disorder (MDD). Despite previous genome-wide association studies (GWAS) of antidepressant treatment response, the underlying genetic factors are unknown. Using prescription data in a population and family-based cohort (Generation Scotland: Scottish Family Health Study; GS:SFHS), we sought to define a measure of (a) antidepressant treatment resistance and (b) stages of antidepressant resistance by inferring antidepressant switching as non-response to treatment. GWAS were conducted separately for antidepressant treatment resistance in GS:SFHS and the Genome-based Therapeutic Drugs for Depression (GENDEP) study and then meta-analysed (meta-analysis n = 4213, cases = 358). For stages of antidepressant resistance, a GWAS on GS:SFHS only was performed (n = 3452). Additionally, we conducted gene-set enrichment, polygenic risk scoring (PRS) and genetic correlation analysis. We did not identify any significant loci, genes or gene sets associated with antidepressant treatment resistance or stages of resistance. Significant positive genetic correlations of antidepressant treatment resistance and stages of resistance with neuroticism, psychological distress, schizotypy and mood disorder traits were identified. These findings suggest that larger sample sizes are needed to identify the genetic architecture of antidepressant treatment response, and that population-based observational studies may provide a tractable approach to achieving the necessary statistical power.

14.
Nat Neurosci ; 22(3): 343-352, 2019 03.
Artigo em Inglês | MEDLINE | ID: mdl-30718901

RESUMO

Major depression is a debilitating psychiatric illness that is typically associated with low mood and anhedonia. Depression has a heritable component that has remained difficult to elucidate with current sample sizes due to the polygenic nature of the disorder. To maximize sample size, we meta-analyzed data on 807,553 individuals (246,363 cases and 561,190 controls) from the three largest genome-wide association studies of depression. We identified 102 independent variants, 269 genes, and 15 genesets associated with depression, including both genes and gene pathways associated with synaptic structure and neurotransmission. An enrichment analysis provided further evidence of the importance of prefrontal brain regions. In an independent replication sample of 1,306,354 individuals (414,055 cases and 892,299 controls), 87 of the 102 associated variants were significant after multiple testing correction. These findings advance our understanding of the complex genetic architecture of depression and provide several future avenues for understanding etiology and developing new treatment approaches.


Assuntos
Depressão/genética , Transtorno Depressivo Maior/genética , Córtex Pré-Frontal/metabolismo , Estudos de Coortes , Feminino , Predisposição Genética para Doença , Variação Genética , Estudo de Associação Genômica Ampla , Humanos , Masculino , Herança Multifatorial , Polimorfismo de Nucleotídeo Único
16.
Nat Genet ; 51(3): 577, 2019 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-30696931

RESUMO

In the version of this article initially published, in Table 2, the descriptions of pathways and definitions in the first and last columns did not correctly correspond to the values in the other columns. The error has been corrected in the HTML and PDF versions of the article.

17.
Neuropsychopharmacology ; 44(4): 757-765, 2019 03.
Artigo em Inglês | MEDLINE | ID: mdl-30559463

RESUMO

Telomere length is a promising biomarker for age-related disease and a potential anti-ageing drug target. Here, we study the genetic architecture of telomere length and the repositioning potential of lithium as an anti-ageing medication. LD score regression applied to the largest telomere length genome-wide association study to-date, revealed SNP-chip heritability estimates of 7.29%, with polygenic risk scoring capturing 4.4% of the variance in telomere length in an independent cohort (p = 6.17 × 10-5). Gene-enrichment analysis identified 13 genes associated with telomere length, with the most significant being the leucine rich repeat gene, LRRC34 (p = 3.69 × 10-18). In the context of lithium, we confirm that chronic use in a sample of 384 bipolar disorder patients is associated with longer telomeres (p = 0.03). As complementary evidence, we studied three orthologs of telomere length regulators in a Caenorhabditis elegans model of lithium-induced extended longevity and found all transcripts to be affected post-treatment (p < 0.05). Lithium may therefore confer its anti-ageing effects by moderating the expression of genes responsible for normal telomere length regulation. This is supported by our bipolar disorder sample, which shows that polygenic risk scores explain a higher proportion of the variance in telomere length amongst chronic lifetime lithium users (variance explained = 8.9%, p = 0.01), compared to non-users (p > 0.05). Consequently, this suggests that lithium may be catalysing the activity of endogenous mechanisms that promote telomere lengthening, whereby its efficacy eventually becomes limited by each individual's inherent telomere maintenance capabilities. Our work indicates a potential use of polygenic risk scoring for the prediction of adult telomere length and consequently lithium's anti-ageing efficacy.

18.
Hum Brain Mapp ; 2018 Dec 04.
Artigo em Inglês | MEDLINE | ID: mdl-30511786

RESUMO

Shorter telomere length (TL) has been associated with the development of mood disorders as well as abnormalities in brain morphology. However, so far, no studies have considered the role TL may have on brain function during tasks relevant to mood disorders. In this study, we examine the relationship between TL and functional brain activation and connectivity, while participants (n = 112) perform a functional magnetic resonance imaging (fMRI) facial affect recognition task. Additionally, because variation in TL has a substantial genetic component we calculated polygenic risk scores for TL to test if they predict face-related functional brain activation. First, our results showed that TL was positively associated with increased activation in the amygdala and cuneus, as well as increased connectivity from posterior regions of the face network to the ventral prefrontal cortex. Second, polygenic risk scores for TL show a positive association with medial prefrontal cortex activation. The data support the view that TL and genetic loading for shorter telomeres, influence the function of brain regions known to be involved in emotional processing.

19.
Front Genet ; 9: 468, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-30459805

RESUMO

Background: Previous studies have revealed associations between psychiatric disorder diagnosis and shorter telomere length. Here, we attempt to discern whether genetic risk for psychiatric disorders, or use of pharmacological treatments (i.e., antidepressants), predict shorter telomere length and risk for aging-related disease in a United Kingdom population sample. Methods: DNA samples from blood were available from 351 participants who were recruited as part of the South East London Community Health (SELCoH) Study, and for which whole-genome genotype data was available. Leukocyte telomere length was characterized using quantitative polymerase chain reactions. Individualized polygenic risk scores for major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ) were calculated using Psychiatric Genomics Consortium summary statistics. We subsequently performed linear models, to discern the impact polygenic risk for psychiatric disorders (an etiological risk factor) and antidepressant use (common pharmacological treatment) have on telomere length, whilst accounting for other lifestyle/health factors (e.g., BMI, smoking). Results: There were no significant associations between polygenic risk for any of the psychiatric disorders tested and telomere length (p > 0.05). Antidepressant use was significantly associated with shorter telomere length and this was independent from a depression diagnosis or current depression severity (p ≤ 0.01). Antidepressant use was also associated with a significantly higher risk of aging-related disease, which was independent from depression diagnosis (p ≤ 0.05). Conclusion: Genetic risk for psychiatric disorders is not associated with shorter telomere length. Further studies are now needed to prospectively characterize if antidepressant use increases risk for aging-related disease and telomere shortening, or whether people who age faster and have aging-related diseases are just more likely to be prescribed antidepressants.

20.
Br J Psychiatry ; : 1-6, 2018 Nov 23.
Artigo em Inglês | MEDLINE | ID: mdl-30468137

RESUMO

BACKGROUND: Treatment-resistant depression (TRD) is the most problematic outcome of depression in terms of functional impairment, suicidal thoughts and decline in physical health.AimsTo investigate the genetic predictors of TRD using a genome-wide approach to contribute to the development of precision medicine. METHOD: A sample recruited by the European Group for the Study of Resistant Depression (GSRD) including 1148 patients with major depressive disorder (MDD) was characterised for the occurrence of TRD (lack of response to at least two adequate antidepressant treatments) and genotyped using the Infinium PsychArray. Three clinically relevant patient groups were considered: TRD, responders and non-responders to the first antidepressant trial, thus outcomes were based on comparisons of these groups. Genetic analyses were performed at the variant, gene and gene-set (i.e. functionally related genes) level. Additive regression models of the outcomes and relevant covariates were used in the GSRD participants and in a fixed-effect meta-analysis performed between GSRD, STAR*D (n = 1316) and GENDEP (n = 761) participants. RESULTS: No individual polymorphism or gene was associated with TRD, although some suggestive signals showed enrichment in cytoskeleton regulation, transcription modulation and calcium signalling. Two gene sets (GO:0043949 and GO:0000183) were associated with TRD versus response and TRD versus response and non-response to the first treatment in the GSRD participants and in the meta-analysis, respectively (corrected P = 0.030 and P = 0.027). CONCLUSIONS: The identified gene sets are involved in cyclic adenosine monophosphate mediated signal and chromatin silencing, two processes previously implicated in antidepressant action. They represent possible biomarkers to implement personalised antidepressant treatments and targets for new antidepressants.Declaration of interestD.S. has received grant/research support from GlaxoSmithKline and Lundbeck; has served as a consultant or on advisory boards for AstraZeneca, Bristol-Myers Squibb, Eli Lilly, Janssen and Lundbeck. S.M. has been a consultant or served on advisory boards for: AstraZeneca, Bristol-Myers Squibb, Forest, Johnson & Johnson, Leo, Lundbeck, Medelink, Neurim, Pierre Fabre, Richter. S.K. has received grant/research support from Eli Lilly, Lundbeck, Bristol-Myers Squibb, GlaxoSmithKline, Organon, Sepracor and Servier; has served as a consultant or on advisory boards for AstraZeneca, Bristol-Myers Squibb, GlaxoSmithKline, Eli Lilly, Lundbeck, Pfizer, Organon, Schwabe, Sepracor, Servier, Janssen and Novartis; and has served on speakers' bureaus for AstraZeneca, Eli Lily, Lundbeck, Schwabe, Sepracor, Servier, Pierre Fabre, Janssen and Neuraxpharm. J.Z. has received grant/research support from Lundbeck, Servier, Brainsway and Pfizer, has served as a consultant or on advisory boards for Servier, Pfizer, Abbott, Lilly, Actelion, AstraZeneca and Roche and has served on speakers' bureaus for Lundbeck, Roch, Lilly, Servier, Pfizer and Abbott. J.M. is a member of the Board of the Lundbeck International Neuroscience Foundation and of Advisory Board of Servier. A.S. is or has been consultant/speaker for: Abbott, AbbVie, Angelini, Astra Zeneca, Clinical Data, Boehringer, Bristol Myers Squibb, Eli Lilly, GlaxoSmithKline, Innovapharma, Italfarmaco, Janssen, Lundbeck, Naurex, Pfizer, Polifarma, Sanofi and Servier. C.M.L. receives research support from RGA UK Services Limited.

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