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1.
Artigo em Inglês | MEDLINE | ID: mdl-33803504

RESUMO

BACKGROUND: African countries have the highest number of people living with HIV (PWH). The continent is home to 12% of the global population, but accounts for 71% of PWH globally. Antiretroviral therapy has played an important role in the reduction of the morbidity and mortality rates for HIV, which necessitates increased surveillance of the threats from pernicious risks to which PWH who live longer remain exposed. This includes cardiopulmonary comorbidities, which pose significant public health and economic challenges. A significant contributor to the cardiopulmonary comorbidities is tobacco smoking. Indeed, globally, PWH have a 2-4-fold higher utilization of tobacco compared to the general population, leading to endothelial dysfunction and atherogenesis that result in cardiopulmonary diseases, such as chronic obstructive pulmonary disease and coronary artery disease. In the context of PWH, we discuss (1) the current trends in cigarette smoking and (2) the lack of geographically relevant data on the cardiopulmonary conditions associated with smoking; we then review (3) the current evidence on chronic inflammation induced by smoking and the potential pathways for cardiopulmonary disease and (4) the multifactorial nature of the syndemic of smoking, HIV, and cardiopulmonary diseases. This commentary calls for a major, multi-setting cohort study using a syndemics framework to assess cardiopulmonary disease outcomes among PWH who smoke. CONCLUSION: We call for a parallel program of implementation research to promote the adoption of evidence-based interventions, which could improve health outcomes for PWH with cardiopulmonary diseases and address the health inequities experienced by PWH in African countries.

2.
Transl Psychiatry ; 11(1): 157, 2021 Mar 04.
Artigo em Inglês | MEDLINE | ID: mdl-33664233

RESUMO

Traditional models of future alcohol use in adolescents have used variable-centered approaches, predicting alcohol use from a set of variables across entire samples or populations. Following the proposition that predictive factors may vary in adolescents as a function of family history, we used a two-pronged approach by first defining clusters of familial risk, followed by prediction analyses within each cluster. Thus, for the first time in adolescents, we tested whether adolescents with a family history of drug abuse exhibit a set of predictors different from adolescents without a family history. We apply this approach to a genetic risk score and individual differences in personality, cognition, behavior (risk-taking and discounting) substance use behavior at age 14, life events, and functional brain imaging, to predict scores on the alcohol use disorders identification test (AUDIT) at age 14 and 16 in a sample of adolescents (N = 1659 at baseline, N = 1327 at follow-up) from the IMAGEN cohort, a longitudinal community-based cohort of adolescents. In the absence of familial risk (n = 616), individual differences in baseline drinking, personality measures (extraversion, negative thinking), discounting behaviors, life events, and ventral striatal activation during reward anticipation were significantly associated with future AUDIT scores, while the overall model explained 22% of the variance in future AUDIT. In the presence of familial risk (n = 711), drinking behavior at age 14, personality measures (extraversion, impulsivity), behavioral risk-taking, and life events were significantly associated with future AUDIT scores, explaining 20.1% of the overall variance. Results suggest that individual differences in personality, cognition, life events, brain function, and drinking behavior contribute differentially to the prediction of future alcohol misuse. This approach may inform more individualized preventive interventions.

3.
Psychol Med ; : 1-9, 2021 Mar 26.
Artigo em Inglês | MEDLINE | ID: mdl-33766168

RESUMO

BACKGROUND: Many studies have reported an increased risk of autism spectrum disorder (ASD) associated with some maternal diagnoses in pregnancy. However, such associations have not been studied systematically, accounting for comorbidity between maternal disorders. Therefore our aim was to comprehensively test the associations between maternal diagnoses around pregnancy and ASD risk in offspring. METHODS: This exploratory case-cohort study included children born in Israel from 1997 to 2008, and followed up until 2015. We used information on all ICD-9 codes received by their mothers during pregnancy and the preceding year. ASD risk associated with each of those conditions was calculated using Cox proportional hazards regression, adjusted for the confounders (birth year, maternal age, socioeconomic status and number of ICD-9 diagnoses during the exposure period). RESULTS: The analytic sample consisted of 80 187 individuals (1132 cases, 79 055 controls), with 822 unique ICD-9 codes recorded in their mothers. After extensive quality control, 22 maternal diagnoses were nominally significantly associated with offspring ASD, with 16 of those surviving subsequent filtering steps (permutation testing, multiple testing correction, multiple regression). Among those, we recorded an increased risk of ASD associated with metabolic [e.g. hypertension; HR = 2.74 (1.92-3.90), p = 2.43 × 10-8], genitourinary [e.g. non-inflammatory disorders of cervix; HR = 1.88 (1.38-2.57), p = 7.06 × 10-5] and psychiatric [depressive disorder; HR = 2.11 (1.32-3.35), p = 1.70 × 10-3] diagnoses. Meanwhile, mothers of children with ASD were less likely to attend prenatal care appointment [HR = 0.62 (0.54-0.71), p = 1.80 × 10-11]. CONCLUSIONS: Sixteen maternal diagnoses were associated with ASD in the offspring, after rigorous filtering of potential false-positive associations. Replication in other cohorts and further research to understand the mechanisms underlying the observed associations with ASD are warranted.

4.
NPJ Schizophr ; 7(1): 2, 2021 Jan 22.
Artigo em Inglês | MEDLINE | ID: mdl-33483511

RESUMO

To characterise the trait-effects of increased genetic risk for schizophrenia, and highlight potential risk mediators, we test the association between schizophrenia polygenic risk scores (PRSs) and 529 behavioural traits (personality, psychological, lifestyle, nutritional) in the UK Biobank. Our primary analysis is performed on individuals aged 38-71 with no history of schizophrenia or related disorders, allowing us to report the effects of schizophrenia genetic risk in the sub-clinical general population. Higher schizophrenia PRSs were associated with a range of traits, including lower verbal-numerical reasoning (P = 6 × 10-61), higher nervous feelings (P = 1 × 10-46) and higher self-reported risk-taking (P = 3 × 10-38). We follow-up the risk-taking association, hypothesising that the association may be due to a genetic propensity for risk-taking leading to greater migration, urbanicity or drug-taking - reported environmental risk factors for schizophrenia, and all positively associated with risk-taking in these data. Next, to identify potential disorder or medication effects, we compare the PRS-trait associations in the general population to the trait values in 599 medicated and non-medicated individuals diagnosed with schizophrenia in the biobank. This analysis highlights, for example, levels of BMI, physical activity and risk-taking in cases in the opposite directions than expected from the PRS-trait associations in the general population. Our analyses offer simple yet potentially revealing insights into the possible causes of observed trait-disorder associations, which can complement approaches such as Mendelian Randomisation. While we urge caution in causal interpretations in PRS cross-trait studies that are highly powered to detect weak horizontal pleiotropy or population structure, we propose that well-designed polygenic score analyses have the potential to highlight modifiable risk factors that lie on the path between genetic risk and disorder.

5.
BMJ Open ; 10(11): e040736, 2020 11 27.
Artigo em Inglês | MEDLINE | ID: mdl-33247020

RESUMO

OBJECTIVE: The COVID-19 pandemic is a global public health crisis, with over 33 million cases and 999 000 deaths worldwide. Data are needed regarding the clinical course of hospitalised patients, particularly in the USA. We aimed to compare clinical characteristic of patients with COVID-19 who had in-hospital mortality with those who were discharged alive. DESIGN: Demographic, clinical and outcomes data for patients admitted to five Mount Sinai Health System hospitals with confirmed COVID-19 between 27 February and 2 April 2020 were identified through institutional electronic health records. We performed a retrospective comparative analysis of patients who had in-hospital mortality or were discharged alive. SETTING: All patients were admitted to the Mount Sinai Health System, a large quaternary care urban hospital system. PARTICIPANTS: Participants over the age of 18 years were included. PRIMARY OUTCOMES: We investigated in-hospital mortality during the study period. RESULTS: A total of 2199 patients with COVID-19 were hospitalised during the study period. As of 2 April, 1121 (51%) patients remained hospitalised, and 1078 (49%) completed their hospital course. Of the latter, the overall mortality was 29%, and 36% required intensive care. The median age was 65 years overall and 75 years in those who died. Pre-existing conditions were present in 65% of those who died and 46% of those discharged. In those who died, the admission median lymphocyte percentage was 11.7%, D-dimer was 2.4 µg/mL, C reactive protein was 162 mg/L and procalcitonin was 0.44 ng/mL. In those discharged, the admission median lymphocyte percentage was 16.6%, D-dimer was 0.93 µg/mL, C reactive protein was 79 mg/L and procalcitonin was 0.09 ng/mL. CONCLUSIONS: In our cohort of hospitalised patients, requirement of intensive care and mortality were high. Patients who died typically had more pre-existing conditions and greater perturbations in inflammatory markers as compared with those who were discharged.

6.
J Med Internet Res ; 22(11): e24018, 2020 11 06.
Artigo em Inglês | MEDLINE | ID: mdl-33027032

RESUMO

BACKGROUND: COVID-19 has infected millions of people worldwide and is responsible for several hundred thousand fatalities. The COVID-19 pandemic has necessitated thoughtful resource allocation and early identification of high-risk patients. However, effective methods to meet these needs are lacking. OBJECTIVE: The aims of this study were to analyze the electronic health records (EHRs) of patients who tested positive for COVID-19 and were admitted to hospitals in the Mount Sinai Health System in New York City; to develop machine learning models for making predictions about the hospital course of the patients over clinically meaningful time horizons based on patient characteristics at admission; and to assess the performance of these models at multiple hospitals and time points. METHODS: We used Extreme Gradient Boosting (XGBoost) and baseline comparator models to predict in-hospital mortality and critical events at time windows of 3, 5, 7, and 10 days from admission. Our study population included harmonized EHR data from five hospitals in New York City for 4098 COVID-19-positive patients admitted from March 15 to May 22, 2020. The models were first trained on patients from a single hospital (n=1514) before or on May 1, externally validated on patients from four other hospitals (n=2201) before or on May 1, and prospectively validated on all patients after May 1 (n=383). Finally, we established model interpretability to identify and rank variables that drive model predictions. RESULTS: Upon cross-validation, the XGBoost classifier outperformed baseline models, with an area under the receiver operating characteristic curve (AUC-ROC) for mortality of 0.89 at 3 days, 0.85 at 5 and 7 days, and 0.84 at 10 days. XGBoost also performed well for critical event prediction, with an AUC-ROC of 0.80 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. In external validation, XGBoost achieved an AUC-ROC of 0.88 at 3 days, 0.86 at 5 days, 0.86 at 7 days, and 0.84 at 10 days for mortality prediction. Similarly, the unimputed XGBoost model achieved an AUC-ROC of 0.78 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. Trends in performance on prospective validation sets were similar. At 7 days, acute kidney injury on admission, elevated LDH, tachypnea, and hyperglycemia were the strongest drivers of critical event prediction, while higher age, anion gap, and C-reactive protein were the strongest drivers of mortality prediction. CONCLUSIONS: We externally and prospectively trained and validated machine learning models for mortality and critical events for patients with COVID-19 at different time horizons. These models identified at-risk patients and uncovered underlying relationships that predicted outcomes.


Assuntos
Infecções por Coronavirus/diagnóstico , Infecções por Coronavirus/mortalidade , Aprendizado de Máquina/normas , Pneumonia Viral/diagnóstico , Pneumonia Viral/mortalidade , Lesão Renal Aguda/epidemiologia , Adolescente , Adulto , Idoso , Idoso de 80 Anos ou mais , Betacoronavirus , Estudos de Coortes , Registros Eletrônicos de Saúde , Feminino , Mortalidade Hospitalar , Hospitalização/estatística & dados numéricos , Hospitais , Humanos , Masculino , Pessoa de Meia-Idade , Cidade de Nova Iorque/epidemiologia , Pandemias , Prognóstico , Curva ROC , Medição de Risco/métodos , Medição de Risco/normas , Adulto Jovem
7.
BMJ Open ; 10(10): e040441, 2020 10 26.
Artigo em Inglês | MEDLINE | ID: mdl-33109676

RESUMO

OBJECTIVE: To assess association of clinical features on COVID-19 patient outcomes. DESIGN: Retrospective observational study using electronic medical record data. SETTING: Five member hospitals from the Mount Sinai Health System in New York City (NYC). PARTICIPANTS: 28 336 patients tested for SARS-CoV-2 from 24 February 2020 to 15 April 2020, including 6158 laboratory-confirmed COVID-19 cases. MAIN OUTCOMES AND MEASURES: Positive test rates and in-hospital mortality were assessed for different racial groups. Among positive cases admitted to the hospital (N=3273), we estimated HR for both discharge and death across various explanatory variables, including patient demographics, hospital site and unit, smoking status, vital signs, lab results and comorbidities. RESULTS: Hispanics (29%) and African Americans (25%) had disproportionately high positive case rates relative to their representation in the overall NYC population (p<0.05); however, no differences in mortality rates were observed in hospitalised patients based on race. Outcomes differed significantly between hospitals (Gray's T=248.9; p<0.05), reflecting differences in average baseline age and underlying comorbidities. Significant risk factors for mortality included age (HR 1.05, 95% CI 1.04 to 1.06; p=1.15e-32), oxygen saturation (HR 0.985, 95% CI 0.982 to 0.988; p=1.57e-17), care in intensive care unit areas (HR 1.58, 95% CI 1.29 to 1.92; p=7.81e-6) and elevated creatinine (HR 1.75, 95% CI 1.47 to 2.10; p=7.48e-10), white cell count (HR 1.02, 95% CI 1.01 to 1.04; p=8.4e-3) and body mass index (BMI) (HR 1.02, 95% CI 1.00 to 1.03; p=1.09e-2). Deceased patients were more likely to have elevated markers of inflammation. CONCLUSIONS: While race was associated with higher risk of infection, we did not find racial disparities in inpatient mortality suggesting that outcomes in a single tertiary care health system are comparable across races. In addition, we identified key clinical features associated with reduced mortality and discharge. These findings could help to identify which COVID-19 patients are at greatest risk of a severe infection response and predict survival.


Assuntos
Betacoronavirus/isolamento & purificação , Infecções por Coronavirus , Hospitalização/estatística & dados numéricos , Unidades de Terapia Intensiva/estatística & dados numéricos , Pandemias , Pneumonia Viral , Fatores Etários , Técnicas de Laboratório Clínico/estatística & dados numéricos , Comorbidade , Infecções por Coronavirus/diagnóstico , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/terapia , Registros Eletrônicos de Saúde/estatística & dados numéricos , Grupos Étnicos , Feminino , Mortalidade Hospitalar , Humanos , Masculino , Pessoa de Meia-Idade , Mortalidade , Cidade de Nova Iorque/epidemiologia , Pneumonia Viral/epidemiologia , Pneumonia Viral/terapia , Estudos Retrospectivos , Fatores de Risco
8.
Cell Death Dis ; 11(10): 930, 2020 Oct 29.
Artigo em Inglês | MEDLINE | ID: mdl-33122623

RESUMO

RAS mutant (MT) metastatic colorectal cancer (mCRC) is resistant to MEK1/2 inhibition and remains a difficult-to-treat group. Therefore, there is an unmet need for novel treatment options for RASMT mCRC. RALA and RALB GTPases function downstream of RAS and have been found to be key regulators of several cell functions implicated in KRAS-driven tumorigenesis. However, their role as regulators of the apoptotic machinery remains to be elucidated. Here, we found that inhibition of RALB expression, but not RALA, resulted in Caspase-8-dependent cell death in KRASMT CRC cells, which was not further increased following MEK1/2 inhibition. Proteomic analysis and mechanistic studies revealed that RALB depletion induced a marked upregulation of the pro-apoptotic cell surface TRAIL Death Receptor 5 (DR5) (also known as TRAIL-R2), primarily through modulating DR5 protein lysosomal degradation. Moreover, DR5 knockdown or knockout attenuated siRALB-induced apoptosis, confirming the role of the extrinsic apoptotic pathway as a regulator of siRALB-induced cell death. Importantly, TRAIL treatment resulted in the association of RALB with the death-inducing signalling complex (DISC) and targeting RALB using pharmacologic inhibition or RNAi approaches triggered a potent increase in TRAIL-induced cell death in KRASMT CRC cells. Significantly, high RALB mRNA levels were found in the poor prognostic Colorectal Cancer Intrinsic Subtypes (CRIS)-B CRC subgroup. Collectively, this study provides to our knowledge the first evidence for a role for RALB in apoptotic priming and suggests that RALB inhibition may be a promising strategy to improve response to TRAIL treatment in poor prognostic RASMT CRIS-B CRC.

9.
Ann Neurol ; 2020 Sep 29.
Artigo em Inglês | MEDLINE | ID: mdl-32996171

RESUMO

OBJECTIVE: The purpose of this study was to infer causal relationships between 22 previously reported risk factors for Alzheimer's disease (AD) and the "AD phenome": AD, AD age of onset (AAOS), hippocampal volume, cortical surface area and thickness, cerebrospinal fluid (CSF) levels of amyloid-ß (Aß42 ), tau, and ptau181 , and the neuropathological burden of neuritic plaques, neurofibrillary tangles (NFTs), and vascular brain injury (VBI). METHODS: Polygenic risk scores (PRS) for the 22 risk factors were computed in 26,431 AD cases/controls and the association with AD was evaluated using logistic regression. Two-sample Mendelian randomization (MR) was used to infer the causal effect of risk factors on the AD phenome. RESULTS: PRS for increased education and diastolic blood pressure were associated with reduced risk for AD. MR indicated that only education was causally associated with reduced risk of AD, delayed AAOS, and increased cortical surface area and thickness. Total- and LDL-cholesterol levels were causally associated with increased neuritic plaque burden, although the effects were driven by single nucleotide polymorphisms (SNPs) within the APOE locus. Diastolic blood pressure and pulse pressure are causally associated with increased risk of VBI. Furthermore, total cholesterol was associated with decreased hippocampal volume; smoking initiation with decreased cortical thickness; type 2 diabetes with an earlier AAOS; and sleep duration with increased cortical thickness. INTERPRETATION: Our comprehensive examination of the genetic evidence for the causal relationships between previously reported risk factors in AD using PRS and MR supports a causal role for education, blood pressure, cholesterol levels, smoking, and diabetes with the AD phenome. ANN NEUROL 2020.

10.
Nat Protoc ; 15(9): 2759-2772, 2020 09.
Artigo em Inglês | MEDLINE | ID: mdl-32709988

RESUMO

A polygenic score (PGS) or polygenic risk score (PRS) is an estimate of an individual's genetic liability to a trait or disease, calculated according to their genotype profile and relevant genome-wide association study (GWAS) data. While present PRSs typically explain only a small fraction of trait variance, their correlation with the single largest contributor to phenotypic variation-genetic liability-has led to the routine application of PRSs across biomedical research. Among a range of applications, PRSs are exploited to assess shared etiology between phenotypes, to evaluate the clinical utility of genetic data for complex disease and as part of experimental studies in which, for example, experiments are performed that compare outcomes (e.g., gene expression and cellular response to treatment) between individuals with low and high PRS values. As GWAS sample sizes increase and PRSs become more powerful, PRSs are set to play a key role in research and stratified medicine. However, despite the importance and growing application of PRSs, there are limited guidelines for performing PRS analyses, which can lead to inconsistency between studies and misinterpretation of results. Here, we provide detailed guidelines for performing and interpreting PRS analyses. We outline standard quality control steps, discuss different methods for the calculation of PRSs, provide an introductory online tutorial, highlight common misconceptions relating to PRS results, offer recommendations for best practice and discuss future challenges.


Assuntos
Predisposição Genética para Doença/genética , Guias de Prática Clínica como Assunto , Medição de Risco/métodos , Humanos , Controle de Qualidade
11.
medRxiv ; 2020 Apr 23.
Artigo em Inglês | MEDLINE | ID: mdl-32511655

RESUMO

BACKGROUND: The coronavirus 2019 (Covid-19) pandemic is a global public health crisis, with over 1.6 million cases and 95,000 deaths worldwide. Data are needed regarding the clinical course of hospitalized patients, particularly in the United States. Methods Demographic, clinical, and outcomes data for patients admitted to five Mount Sinai Health System hospitals with confirmed Covid-19 between February 27 and April 2, 2020 were identified through institutional electronic health records. We conducted a descriptive study of patients who had in-hospital mortality or were discharged alive. Results A total of 2,199 patients with Covid-19 were hospitalized during the study period. As of April 2nd, 1,121 (51%) patients remained hospitalized, and 1,078 (49%) completed their hospital course. Of the latter, the overall mortality was 29%, and 36% required intensive care. The median age was 65 years overall and 75 years in those who died. Pre-existing conditions were present in 65% of those who died and 46% of those discharged. In those who died, the admission median lymphocyte percentage was 11.7%, D-dimer was 2.4 ug/ml, C-reactive protein was 162 mg/L, and procalcitonin was 0.44 ng/mL. In those discharged, the admission median lymphocyte percentage was 16.6%, D-dimer was 0.93 ug/ml, C-reactive protein was 79 mg/L, and procalcitonin was 0.09 ng/mL. Conclusions This is the largest and most diverse case series of hospitalized patients with Covid-19 in the United States to date. Requirement of intensive care and mortality were high. Patients who died typically had pre-existing conditions and severe perturbations in inflammatory markers.

13.
Mol Psychiatry ; 25(7): 1430-1446, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-31969693

RESUMO

Depression is more frequent among individuals exposed to traumatic events. Both trauma exposure and depression are heritable. However, the relationship between these traits, including the role of genetic risk factors, is complex and poorly understood. When modelling trauma exposure as an environmental influence on depression, both gene-environment correlations and gene-environment interactions have been observed. The UK Biobank concurrently assessed Major Depressive Disorder (MDD) and self-reported lifetime exposure to traumatic events in 126,522 genotyped individuals of European ancestry. We contrasted genetic influences on MDD stratified by reported trauma exposure (final sample size range: 24,094-92,957). The SNP-based heritability of MDD with reported trauma exposure (24%) was greater than MDD without reported trauma exposure (12%). Simulations showed that this is not confounded by the strong, positive genetic correlation observed between MDD and reported trauma exposure. We also observed that the genetic correlation between MDD and waist circumference was only significant in individuals reporting trauma exposure (rg = 0.24, p = 1.8 × 10-7 versus rg = -0.05, p = 0.39 in individuals not reporting trauma exposure, difference p = 2.3 × 10-4). Our results suggest that the genetic contribution to MDD is greater when reported trauma is present, and that a complex relationship exists between reported trauma exposure, body composition, and MDD.

14.
Int J Epidemiol ; 49(1): 233-243, 2020 02 01.
Artigo em Inglês | MEDLINE | ID: mdl-31074781

RESUMO

BACKGROUND: Maternal pre-pregnancy body mass index (BMI) is positively associated with offspring birth weight (BW) and BMI in childhood and adulthood. Each of these associations could be due to causal intrauterine effects, or confounding (genetic or environmental), or some combination of these. Here we estimate the extent to which the association between maternal BMI and offspring body size is explained by offspring genotype, as a first step towards establishing the importance of genetic confounding. METHODS: We examined the associations of maternal pre-pregnancy BMI with offspring BW and BMI at 1, 5, 10 and 15 years, in three European birth cohorts (n ≤11 498). Bivariate Genomic-relatedness-based Restricted Maximum Likelihood implemented in the GCTA software (GCTA-GREML) was used to estimate the extent to which phenotypic covariance was explained by offspring genotype as captured by common imputed single nucleotide polymorphisms (SNPs). We merged individual participant data from all cohorts, enabling calculation of pooled estimates. RESULTS: Phenotypic covariance (equivalent here to Pearson's correlation coefficient) between maternal BMI and offspring phenotype was 0.15 [95% confidence interval (CI): 0.13, 0.17] for offspring BW, increasing to 0.29 (95% CI: 0.26, 0.31) for offspring 15 year BMI. Covariance explained by offspring genotype was negligible for BW [-0.04 (95% CI: -0.09, 0.01)], but increased to 0.12 (95% CI: 0.04, 0.21) at 15 years, which is equivalent to 43% (95% CI: 15%, 72%) of the phenotypic covariance. Sensitivity analyses using weight, BMI and ponderal index as the offspring phenotype at all ages showed similar results. CONCLUSIONS: Offspring genotype explains a substantial fraction of the covariance between maternal BMI and offspring adolescent BMI. This is consistent with a potentially important role for genetic confounding as a driver of the maternal BMI-offspring BMI association.


Assuntos
Peso ao Nascer/genética , Índice de Massa Corporal , Mães , Obesidade/etiologia , Obesidade Pediátrica/genética , Adulto , Criança , Feminino , Humanos , Masculino , Obesidade/genética , Gravidez
15.
Addiction ; 115(3): 482-492, 2020 03.
Artigo em Inglês | MEDLINE | ID: mdl-31833150

RESUMO

BACKGROUND AND AIMS: The use of cannabis has previously been linked to both depression and self-harm; however, the role of genetics in this relationship is unclear. This study aimed to estimate the phenotypic and genetic associations between cannabis use and depression and self-harm. DESIGN: Cross-sectional data collected through UK Biobank were used to test the phenotypic association between cannabis use, depression and self-harm. UK Biobank genetic data were then combined with consortia genome-wide association study summary statistics to further test the genetic relationships between these traits using LD score regression, polygenic risk scoring and Mendelian randomization methods. SETTING: United Kingdom, with additional international consortia data. PARTICIPANTS: A total of 126 291 British adults aged between 40 and 70 years, recruited into UK Biobank. MEASUREMENTS: Phenotypic outcomes were life-time history of cannabis use (including initial and continued cannabis use), depression (including single-episode and recurrent depression) and self-harm. Genome-wide genetic data were used and assessment centre, batch and the first six principal components were included as key covariates when handling genetic data. FINDINGS: In UK Biobank, cannabis use is associated with an increased likelihood of depression [odds ratio (OR) = 1.64, 95% confidence interval (CI) = 1.59-1.70] and self-harm (OR = 2.85, 95% CI = 2.69-3.01). The strength of this phenotypic association is stronger when more severe trait definitions of cannabis use and depression are considered. Using consortia genome-wide summary statistics, significant genetic correlations are seen between cannabis use and depression [rg = 0.289, standard error (SE) = 0.036]. Polygenic risk scores for cannabis use and depression explain a small but significant proportion of variance in cannabis use, depression and self-harm within a UK Biobank target sample. However, two-sample Mendelian randomization analyses were not significant. CONCLUSIONS: Cannabis use appeared to be both phenotypically and genetically associated with depression and self-harm. Limitations in statistical power mean that conclusions could not be made on the direction of causality between these traits.

16.
Cancers (Basel) ; 11(12)2019 Dec 17.
Artigo em Inglês | MEDLINE | ID: mdl-31861091

RESUMO

High expression of the HOXA cluster correlates with poor clinical outcome in acute myeloid leukemias, particularly those harboring rearrangements of the mixed-lineage-leukemia gene (MLLr). Whilst decreased HOXA expression acts as a readout for candidate experimental therapies, the necessity of the HOXA cluster for leukemia maintenance has not been fully explored. Primary leukemias were generated in hematopoietic stem/progenitor cells from Cre responsive transgenic mice for conditional deletion of the Hoxa locus. Hoxa deletion resulted in reduced proliferation and colony formation in which surviving leukemic cells retained at least one copy of the Hoxa cluster, indicating dependency. Comparative transcriptome analysis of Hoxa wild type and deleted leukemic cells identified a unique gene signature associated with key pathways including transcriptional mis-regulation in cancer, the Fanconi anemia pathway and cell cycle progression. Further bioinformatics analysis of the gene signature identified a number of candidate FDA-approved drugs for potential repurposing in high HOXA expressing cancers including MLLr leukemias. Together these findings support dependency for an MLLr leukemia on Hoxa expression and identified candidate drugs for further therapeutic evaluation.

17.
Nat Commun ; 10(1): 5765, 2019 12 18.
Artigo em Inglês | MEDLINE | ID: mdl-31852892

RESUMO

Body composition is often altered in psychiatric disorders. Using genome-wide common genetic variation data, we calculate sex-specific genetic correlations amongst body fat %, fat mass, fat-free mass, physical activity, glycemic traits and 17 psychiatric traits (up to N = 217,568). Two patterns emerge: (1) anorexia nervosa, schizophrenia, obsessive-compulsive disorder, and education years are negatively genetically correlated with body fat % and fat-free mass, whereas (2) attention-deficit/hyperactivity disorder (ADHD), alcohol dependence, insomnia, and heavy smoking are positively correlated. Anorexia nervosa shows a stronger genetic correlation with body fat % in females, whereas education years is more strongly correlated with fat mass in males. Education years and ADHD show genetic overlap with childhood obesity. Mendelian randomization identifies schizophrenia, anorexia nervosa, and higher education as causal for decreased fat mass, with higher body fat % possibly being a causal risk factor for ADHD and heavy smoking. These results suggest new possibilities for targeted preventive strategies.


Assuntos
Glicemia/genética , Composição Corporal/genética , Transtornos Mentais/genética , Sobrepeso/genética , Fatores Etários , Comorbidade , Escolaridade , Feminino , Variação Genética , Estudo de Associação Genômica Ampla , Humanos , Masculino , Transtornos Mentais/epidemiologia , Transtornos Mentais/prevenção & controle , Pessoa de Meia-Idade , Herança Multifatorial/genética , Sobrepeso/epidemiologia , Fenótipo , Aptidão Física , Fatores de Risco , Fatores Sexuais
18.
Front Med (Lausanne) ; 6: 185, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31632973

RESUMO

There has been an exponential growth in the application of AI in health and in pathology. This is resulting in the innovation of deep learning technologies that are specifically aimed at cellular imaging and practical applications that could transform diagnostic pathology. This paper reviews the different approaches to deep learning in pathology, the public grand challenges that have driven this innovation and a range of emerging applications in pathology. The translation of AI into clinical practice will require applications to be embedded seamlessly within digital pathology workflows, driving an integrated approach to diagnostics and providing pathologists with new tools that accelerate workflow and improve diagnostic consistency and reduce errors. The clearance of digital pathology for primary diagnosis in the US by some manufacturers provides the platform on which to deliver practical AI. AI and computational pathology will continue to mature as researchers, clinicians, industry, regulatory organizations and patient advocacy groups work together to innovate and deliver new technologies to health care providers: technologies which are better, faster, cheaper, more precise, and safe.

19.
Nat Commun ; 10(1): 4222, 2019 09 17.
Artigo em Inglês | MEDLINE | ID: mdl-31530810

RESUMO

Inversions are one type of structural variants linked to phenotypic differences and adaptation in multiple organisms. However, there is still very little information about polymorphic inversions in the human genome due to the difficulty of their detection. Here, we develop a new high-throughput genotyping method based on probe hybridization and amplification, and we perform a complete study of 45 common human inversions of 0.1-415 kb. Most inversions promoted by homologous recombination occur recurrently in humans and great apes and they are not tagged by SNPs. Furthermore, there is an enrichment of inversions showing signatures of positive or balancing selection, diverse functional effects, such as gene disruption and gene-expression changes, or association with phenotypic traits. Therefore, our results indicate that the genome is more dynamic than previously thought and that human inversions have important functional and evolutionary consequences, making possible to determine for the first time their contribution to complex traits.


Assuntos
Inversão Cromossômica , Evolução Molecular , Genoma Humano , Técnicas de Genotipagem , Humanos , Fenótipo , Polimorfismo de Nucleotídeo Único
20.
Gynecol Oncol ; 155(2): 305-317, 2019 11.
Artigo em Inglês | MEDLINE | ID: mdl-31493898

RESUMO

OBJECTIVE: High grade serous carcinoma (HGSC) is the most common and most aggressive, subtype of epithelial ovarian cancer. It presents as advanced stage disease with poor prognosis. Recent pathological evidence strongly suggests HGSC arises from the fallopian tube via the precursor lesion; serous tubal intraepithelial carcinoma (STIC). However, further definition of the molecular evolution of HGSC has major implications for both clinical management and research. This study aims to more clearly define the molecular pathogenesis of HGSC. METHODS: Six cases of HGSC were identified at the Northern Ireland Gynaecological Cancer Centre (NIGCC) that each contained ovarian HGSC (HGSC), omental HGSC (OMT), STIC, normal fallopian tube epithelium (FTE) and normal ovarian surface epithelium (OSE). The relevant formalin-fixed paraffin embedded (FFPE) tissue samples were retrieved from the pathology archive via the Northern Ireland Biobank following attaining ethical approval (NIB11:005). Full microarray-based gene expression profiling was performed on the cohort. The resulting data was analysed bioinformatically and the results were validated in a HGSC-specific in-vitro model. RESULTS: The carcinogenesis of HGSC was investigated and showed the molecular profile of HGSC to be more closely related to normal FTE than OSE. STIC lesions also clustered closely with HGSC, indicating a common molecular origin. CONCLUSION: This study provides strong evidence suggesting that extrauterine HGSC arises from the fimbria of the distal fallopian tube. Furthermore, several potential pathways were identified which could be targeted by novel therapies for HGSC. These findings have significant translational relevance for both primary prevention and clinical management of the disease.


Assuntos
Cistadenocarcinoma Seroso/patologia , Neoplasias Ovarianas/patologia , Linhagem Celular Tumoral , Transformação Celular Neoplásica/patologia , Cistadenocarcinoma Seroso/genética , Cistadenocarcinoma Seroso/mortalidade , Intervalo Livre de Doença , Tubas Uterinas/patologia , Feminino , Perfilação da Expressão Gênica , Genes Neoplásicos/genética , Humanos , Neoplasias Ovarianas/genética , Neoplasias Ovarianas/mortalidade , Regulação para Cima/fisiologia
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