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Nevin Manimala Statistics

The role of HIRA-dependent H3.3 deposition and its modifications in the somatic hypermutation of immunoglobulin variable regions

Proc Natl Acad Sci U S A. 2021 Dec 14;118(50):e2114743118. doi: 10.1073/pnas.2114743118.

ABSTRACT

The H3.3 histone variant and its chaperone HIRA are involved in active transcription, but their detailed roles in regulating somatic hypermutation (SHM) of immunoglobulin variable regions in human B cells are not yet fully understood. In this study, we show that the knockout (KO) of HIRA significantly decreased SHM and changed the mutation pattern of the variable region of the immunoglobulin heavy chain (IgH) in the human Ramos B cell line without changing the levels of activation-induced deaminase and other major proteins known to be involved in SHM. Except for H3K79me2/3 and Spt5, many factors related to active transcription, including H3.3, were substantively decreased in HIRA KO cells, and this was accompanied by decreased nascent transcription in the IgH locus. The abundance of ZMYND11 that specifically binds to H3.3K36me3 on the IgH locus was also reduced in the HIRA KO. Somewhat surprisingly, HIRA loss increased the chromatin accessibility of the IgH V region locus. Furthermore, stable expression of ectopic H3.3G34V and H3.3G34R mutants that inhibit both the trimethylation of H3.3K36 and the recruitment of ZMYND11 significantly reduced SHM in Ramos cells, while the H3.3K79M did not. Consistent with the HIRA KO, the H3.3G34V mutant also decreased the occupancy of various elongation factors and of ZMYND11 on the IgH variable and downstream switching regions. Our results reveal an unrecognized role of HIRA and the H3.3K36me3 modification in SHM and extend our knowledge of how transcription-associated chromatin structure and accessibility contribute to SHM in human B cells.

PMID:34873043 | DOI:10.1073/pnas.2114743118

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Nevin Manimala Statistics

Interrupted time series analyses to assess the impact of alcohol control policy on socioeconomic inequalities in mortality in Lithuania: a study protocol

BMJ Open. 2021 Dec 6;11(12):e053497. doi: 10.1136/bmjopen-2021-053497.

ABSTRACT

INTRODUCTION: Alcohol use is a major risk factor for mortality. Previous studies suggest that the alcohol-attributable mortality burden is higher in lower socioeconomic strata. This project will test the hypothesis that the 2017 increase of alcohol excise taxes linked to lower all-cause mortality rates in previous analyses will reduce socioeconomic mortality inequalities.

METHODS AND ANALYSIS: Data on all causes of deaths will be obtained from Statistics Lithuania. Record linkage will be implemented using personal identifiers combining data from (1) the 2011 whole-population census, (2) death records between 1 March 2011 (census date) and 31 December 2019, and (3) emigration records, for individuals aged 40-70 years. The analyses will be performed separately for all-cause and for alcohol-attributable deaths. Monthly age-standardised mortality rates will be calculated by sex, education and three measures of socioeconomic status (SES). Inequalities in mortality will be assessed using absolute and relative indicators between low and high SES groups. We will perform interrupted time series analyses, and test the impact of the 2017 rise in alcohol excise taxation using generalised additive mixed models. In these models, we will control for secular trends for economic development.

ETHICS AND DISSEMINATION: This work is part of project grant 1R01AA028224-01 by the National Institute on Alcohol Abuse and Alcoholism. It has been granted research ethics approval 050/2020 by Centre for Addiction and Mental Health Research Ethics Board on 17 April 2020, renewed on 30 March 2021. The time series of mortality inequalities as well as the statistical code will be made publicly available, allowing other researchers to adapt the proposed method to other jurisdictions.

PMID:34873010 | DOI:10.1136/bmjopen-2021-053497

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Nevin Manimala Statistics

Biomarker discovery studies for patient stratification using machine learning analysis of omics data: a scoping review

BMJ Open. 2021 Dec 6;11(12):e053674. doi: 10.1136/bmjopen-2021-053674.

ABSTRACT

OBJECTIVE: To review biomarker discovery studies using omics data for patient stratification which led to clinically validated FDA-cleared tests or laboratory developed tests, in order to identify common characteristics and derive recommendations for future biomarker projects.

DESIGN: Scoping review.

METHODS: We searched PubMed, EMBASE and Web of Science to obtain a comprehensive list of articles from the biomedical literature published between January 2000 and July 2021, describing clinically validated biomarker signatures for patient stratification, derived using statistical learning approaches. All documents were screened to retain only peer-reviewed research articles, review articles or opinion articles, covering supervised and unsupervised machine learning applications for omics-based patient stratification. Two reviewers independently confirmed the eligibility. Disagreements were solved by consensus. We focused the final analysis on omics-based biomarkers which achieved the highest level of validation, that is, clinical approval of the developed molecular signature as a laboratory developed test or FDA approved tests.

RESULTS: Overall, 352 articles fulfilled the eligibility criteria. The analysis of validated biomarker signatures identified multiple common methodological and practical features that may explain the successful test development and guide future biomarker projects. These include study design choices to ensure sufficient statistical power for model building and external testing, suitable combinations of non-targeted and targeted measurement technologies, the integration of prior biological knowledge, strict filtering and inclusion/exclusion criteria, and the adequacy of statistical and machine learning methods for discovery and validation.

CONCLUSIONS: While most clinically validated biomarker models derived from omics data have been developed for personalised oncology, first applications for non-cancer diseases show the potential of multivariate omics biomarker design for other complex disorders. Distinctive characteristics of prior success stories, such as early filtering and robust discovery approaches, continuous improvements in assay design and experimental measurement technology, and rigorous multicohort validation approaches, enable the derivation of specific recommendations for future studies.

PMID:34873011 | DOI:10.1136/bmjopen-2021-053674

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Nevin Manimala Statistics

Causes of infective endocarditis in the Western Cape, South Africa: a prospective cohort study using a set protocol for organism detection and central decision making by an endocarditis team

BMJ Open. 2021 Dec 6;11(12):e053169. doi: 10.1136/bmjopen-2021-053169.

ABSTRACT

BACKGROUND: Blood culture negative infective endocarditis (BCNIE) poses both a diagnostic and therapeutic challenge. High rates of BCNIE reported in South Africa have been attributed to antibiotic use prior to blood culture sampling.

OBJECTIVES: To assess the impact of a systematic approach to organism detection and identify the causes of infective endocarditis (IE), in particular causes of BCNIE.

DESIGN: Prospective cohort study.

METHODS: The Tygerberg Endocarditis Cohort study prospectively enrolled patients with IE between November 2019 and February 2021. A set protocol for organism detection with management of patients by an endocarditis team was employed. This prospective cohort was compared with a retrospective cohort of patients with IE admitted between January 2017 and December 2018.

RESULTS: One hundred and forty patients with IE were included, with 75 and 65 patients in the retrospective and prospective cohorts, respectively. Baseline demographic characteristics were similar with a mean age of 39.6 years and male predominance (male sex=67.1%). The rate of BCNIE was lower in the prospective group (28/65 or 43.1%) compared with the retrospective group (47/75 or 62.7%; p=0.039). The BCNIE in-hospital mortality rate in the retrospective cohort was 23.4% compared with 14.2% in the prospective cohort (p=0.35). A cause was identified (including non-culture techniques) in 86.2% of patients in the prospective cohort, with Staphylococcus aureus (26.2%), Bartonella species (20%) and the viridans streptococci (15.3%) being most common.

CONCLUSION: The introduction of a set protocol for organism detection, managed by an endocarditis team, has identified Staphylococcusaureus as the most common cause of IE and identified non-culturable organisms, in particular Bartonella quintana, as an important cause of BCNIE. A reduction in in-hospital mortality in patients with BCNIE was observed, but did not reach statistical significance.

PMID:34873007 | DOI:10.1136/bmjopen-2021-053169

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Nevin Manimala Statistics

Validity and reliability of the diagnostic codes for hypochondriasis and dysmorphophobia in the Swedish National Patient Register: a retrospective chart review

BMJ Open. 2021 Dec 6;11(12):e051853. doi: 10.1136/bmjopen-2021-051853.

ABSTRACT

OBJECTIVES: In the International Classification of Diseases, Tenth Edition (ICD-10), hypochondriasis (illness anxiety disorder) and dysmorphophobia (body dysmorphic disorder) share the same diagnostic code (F45.2). However, the Swedish ICD-10 allows for these disorders to be coded separately (F45.2 and F45.2A, respectively), potentially offering unique opportunities for register-based research on these conditions. We assessed the validity and reliability of their ICD-10 codes in the Swedish National Patient Register (NPR).

DESIGN: Retrospective chart review.

METHODS: Six hundred individuals with a diagnosis of hypochondriasis or dysmorphophobia (300 each) were randomly selected from the NPR. Their medical files were requested from the corresponding clinics, located anywhere in Sweden. Two independent raters assessed each file according to ICD-10 definitions and Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision and Fifth Edition criteria. Raters also completed the Clinical Global Impression-Severity (CGI-S) and the Global Assessment of Functioning (GAF).

PRIMARY OUTCOME MEASURE: Per cent between-rater agreement and positive predictive value (PPV). Intraclass correlation coefficients for the CGI-S and the GAF.

RESULTS: Eighty-four hypochondriasis and 122 dysmorphophobia files were received and analysed. The inter-rater agreement rate regarding the presence or absence of a diagnosis was 95.2% for hypochondriasis and 92.6% for dysmorphophobia. Sixty-seven hypochondriasis files (79.8%) and 111 dysmorphophobia files (91.0%) were considered ‘true positive’ cases (PPV=0.80 and PPV=0.91, respectively). CGI-S scores indicated that symptoms were moderately to markedly severe, while GAF scores suggested moderate impairment for hypochondriasis cases and moderate to serious impairment for dysmorphophobia cases. CGI-S and GAF inter-rater agreement were good for hypochondriasis and moderate for dysmorphophobia.

CONCLUSIONS: The Swedish ICD-10 codes for hypochondriasis and dysmorphophobia are sufficiently valid and reliable for register-based studies. The results of such studies should be interpreted in the context of a possible over-representation of severe and highly impaired cases in the register, particularly for dysmorphophobia.

PMID:34873001 | DOI:10.1136/bmjopen-2021-051853

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Nevin Manimala Statistics

Relationship between renal function and prognosis of Chinese proliferative diabetic retinopathy patients undergoing the first vitrectomy: protocol for a prospective cohort study

BMJ Open. 2021 Dec 6;11(12):e052417. doi: 10.1136/bmjopen-2021-052417.

ABSTRACT

INTRODUCTION: China has the largest number of adults with diabetes aged 20-79 years (116.4 million) in 2019. Due to the socioeconomic condition or a lack of awareness of diabetic complications, many adults with diabetes have proliferative diabetic retinopathy (PDR) or renal function impairment at their first visit to the clinic for a sudden loss of vision, and pars plana vitrectomy (PPV) is required for their treatment. Risk factors for the outcomes and complications of PPV surgery in PDR patients have been widely explored in many epidemiological studies and clinical trials. However, few prospective studies have analysed the association between renal function and surgical outcomes in PDR.

METHODS AND ANALYSIS: This is a single-centre, prospective cohort study of PDR patients with type 2 diabetes mellitus who have definite indications for PPV surgery with or without renal function impairment. We will consecutively enrol PDR patients who meet the inclusion and exclusion criteria from November 2020 to December 2023. Each participant will be followed up for at least 6 months after surgery. Clinical data from medical records and vitreous fluid will be collected.Demographic characteristics and study outcomes will be summarised using descriptive statistics. The variation will be described and evaluated using the χ² test or Kruskal-Wallis test. Generalise additive mixed models will be used to explore the association between the renal profile and surgical outcomes including BCVA, and retinal and choroidal microvasculature/microstructure. Multivariate ordinal regression analysis will be used to detect the independent association between renal profile and BCVA changes, and smooth curve fitting will be employed to briefly present the tendency.

ETHICS AND DISSEMINATION: The trial has received ethical approval from the West China Hospital of Sichuan University. Results of this trial will be disseminated through publication in peer-reviewed journals and presentations at local and international meetings.

TRIAL REGISTRATION NUMBER: ChiCTR2000039698.

PMID:34873003 | DOI:10.1136/bmjopen-2021-052417

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Nevin Manimala Statistics

Patients’ choice of healthcare providers and predictors of modern healthcare utilisation in Bangladesh: Household Income and Expenditure Survey (HIES) 2016-2017 (BBS)

BMJ Open. 2021 Dec 6;11(12):e051434. doi: 10.1136/bmjopen-2021-051434.

ABSTRACT

OBJECTIVES: The number of modern healthcare providers in Bangladesh has increased and they are well equipped with modern medical instruments and infrastructures. Despite this development, patients seeking treatment from alternative healthcare providers are ongoing. Hence, this study aims to determine the underlying predictors of patients’ choosing modern healthcare providers and health facilities for getting treatments.

SETTING: Data from the nationally representative Household Income and Expenditure Survey 2016-2017 conducted by the Bangladesh Bureau of Statistics were used.

PARTICIPANTS: 34 512 respondents sought treatment for their illnesses from different types of available healthcare providers.

PRIMARY AND SECONDARY OUTCOME MEASURE: Patients’ choice of healthcare providers (primary) and predictors of patients’ choice of modern healthcare providers (secondary).

RESULTS: The study found that 40% of the patients visit modern healthcare providers primarily on having symptoms of illness, and the remainder goes to alternative healthcare providers. Patients living in urban areas (adjusted OR (AOR)=1.11, 95% CI 1.05 to 1.17, p<0.01), and if the travel time was between 1 and 2 hours (AOR=1.11, 95% CI 1.00 to 1.22, p<0.05) compared with travel time less than 1 hour, were positively associated to utilisation of modern healthcare facilities for their first consultation. The statistical models show that the predisposing and need factors do not significantly impact patients’ choice of modern healthcare providers.

CONCLUSIONS: The distribution of modern healthcare providers should be even across the country to eliminate the rural-urban divide in modern healthcare utilisation. Enhancing the digital provision of modern healthcare services could reduce travel time, omit transportation costs and save waiting time for treatment by the modern healthcare providers. Policymakers can think of introducing a national health insurance programme in Bangladesh as a potential policy instrument.

PMID:34873000 | DOI:10.1136/bmjopen-2021-051434

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Nevin Manimala Statistics

Impact of the COVID-19 pandemic on ongoing health research: an ad hoc survey among investigators in Germany

BMJ Open. 2021 Dec 6;11(12):e049086. doi: 10.1136/bmjopen-2021-049086.

ABSTRACT

OBJECTIVES: To gain insights into the impact of the COVID-19 pandemic on ongoing health research projects, using projects from a selected funding programme in Germany as an example.

DESIGN: Online survey and validation workshop.

SETTING: Lockdowns and social distancing policies impact on clinical and public health research in various forms, especially if unrelated to COVID-19. Research institutions have reduced onsite activities, data are often collected remotely, and during the height of the crisis, clinical researchers were partially forced to abandon their projects in favour of front-line care.

PARTICIPANTS SURVEY: 120 investigators of health research projects across Germany, performed between 15 and 25 May 2020; workshop: 32 investigators, performed on 28 May 2020.

RESULTS: The response rate (78%) showed that the survey generated significant interest among investigators. 85 responses were included for analysis, and the majority of investigators (93%) reported that their projects were affected by the pandemic, with many (80%) stating that data collection was not possible as planned, and they could not carry out interventions as intended (67%). Other impacts were caused by staff being unavailable, for example, through child or elder care commitments or because of COVID-19 quarantine or illness. Investigators also reported that publications were delayed or not feasible at all (56%), and some experienced problems with PhD or Masters theses (18%). The majority of investigators had mitigation strategies in place such as adjustment of data collection methods using digital tools (46%) or of project implementation in general (46%), others made changes in research design or research questions (27%).

CONCLUSIONS: The COVID-19 pandemic has severely impacted on health research projects. The main challenge is now to mitigate negative effects and to improve long-term resilience in health research. The pandemic has also acted as a driver of innovation and change, for example, by accelerating the use of digital methods.

PMID:34872995 | DOI:10.1136/bmjopen-2021-049086

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Nevin Manimala Statistics

Effective and scalable single-cell data alignment with non-linear canonical correlation analysis

Nucleic Acids Res. 2021 Dec 6:gkab1147. doi: 10.1093/nar/gkab1147. Online ahead of print.

ABSTRACT

Data alignment is one of the first key steps in single cell analysis for integrating multiple datasets and performing joint analysis across studies. Data alignment is challenging in extremely large datasets, however, as the major of the current single cell data alignment methods are not computationally efficient. Here, we present VIPCCA, a computational framework based on non-linear canonical correlation analysis for effective and scalable single cell data alignment. VIPCCA leverages both deep learning for effective single cell data modeling and variational inference for scalable computation, thus enabling powerful data alignment across multiple samples, multiple data platforms, and multiple data types. VIPCCA is accurate for a range of alignment tasks including alignment between single cell RNAseq and ATACseq datasets and can easily accommodate millions of cells, thereby providing researchers unique opportunities to tackle challenges emerging from large-scale single-cell atlas.

PMID:34871454 | DOI:10.1093/nar/gkab1147

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Nevin Manimala Statistics

DNA methylation variation along the cancer epigenome and the identification of novel epigenetic driver events

Nucleic Acids Res. 2021 Dec 6:gkab1167. doi: 10.1093/nar/gkab1167. Online ahead of print.

ABSTRACT

While large-scale studies applying various statistical approaches have identified hundreds of mutated driver genes across various cancer types, the contribution of epigenetic changes to cancer remains more enigmatic. This is partly due to the fact that certain regions of the cancer genome, due to their genomic and epigenomic properties, are more prone to dysregulated DNA methylation than others. Thus, it has been difficult to distinguish which promoter methylation changes are really driving carcinogenesis from those that are mostly just a reflection of their genomic location. By developing a novel method that corrects for epigenetic covariates, we reveal a small, concise set of potential epigenetic driver events. Interestingly, those changes suggest different modes of epigenetic carcinogenesis: first, we observe recurrent inactivation of known cancer genes across tumour types suggesting a higher convergence on common tumour suppressor pathways than previously anticipated. Second, in prostate cancer, a cancer type with few recurrently mutated genes, we demonstrate how the epigenome primes tumours towards higher tolerance of other aberrations.

PMID:34871444 | DOI:10.1093/nar/gkab1167