https://doi.org/10.1021/acs.jcim.5c02297

2025-11-14

2025-11-14

https://doi.org/10.1101/2025.03.17.25323906

2025-03-20

2025-10-23

https://pubmed.ncbi.nlm.nih.gov/40030473/

Accurate detection and prevalence estimation of behavioral health conditions, such as opioid use disorder (OUD), are crucial for identifying at-risk individuals, determining treatment needs, monitoring prevention and intervention efforts, and recruiting treatment-naive participants for clinical trials. The availability of extensive health data, combined with advancements in machine learning (ML) frameworks, has enabled researchers to employ various ML techniques to predict or identify OUD within patient health data. Ideally, we could directly estimate the prevalence, or the proportion of a population with a condition over time. However, underdiagnosis and undercoding of conditions in patient health records make it challenging to determine the true prevalence of these conditions and to identify at-risk patients with less severe conditions who are more likely to be missed. Consequently, patients without diagnoses may comprise positive and negative examples for a given condition. Treating all undiagnosed (uncoded) patients as negative when applying ML methods can introduce bias into models, affecting their predictive power. To address this issue, we employed Positive Unlabeled Learning Selected Not At Random (PULSNAR), a Positive and Unlabeled (PU) learning technique, to estimate the probability of a given patient having OUD during a time window and the overall population prevalence of OUD. In a sample of 3,342,044 commercially insured US patients with at least one opioid prescription filled, PULSNAR estimated that 5.08% of patients have a cumulative prevalence of OUD over a 2-5 a observation period, compared to the 1.35% with a recorded OUD diagnosis, with 73.5% of cases not diagnosed/coded. The prevalence estimates provided by PULSNAR are consistent with those reported in other studies.

2025-06-14

2025-06-14

https://europepmc.org/articles/PMC11762411

This study reports a comprehensive environmental scan of the generative AI (GenAI) infrastructure in the national network for clinical and translational science across 36 institutions supported by the CTSA Program led by the National Center for Advancing Translational Sciences (NCATS) of the National Institutes of Health (NIH) at the United States. Key findings indicate a diverse range of institutional strategies, with most organizations in the experimental phase of GenAI deployment. The results underscore the need for a more coordinated approach to GenAI governance, emphasizing collaboration among senior leaders, clinicians, information technology staff, and researchers. Our analysis reveals that 53% of institutions identified data security as a primary concern, followed by lack of clinician trust (50%) and AI bias (44%), which must be addressed to ensure the ethical and effective implementation of GenAI technologies.

2025-06-14

2025-06-14

https://doi.org/10.7717/peerj-cs.2451

2024-11-05

2024-11-05

https://doi.org/10.3390/pathogens13100867

2024-10-03

2024-10-03

https://europepmc.org/articles/PMC10498606

BackgroundPlasmodium falciparum malaria is a leading cause of pediatric morbidity and mortality in holoendemic transmission areas. Severe malarial anemia [SMA, hemoglobin (Hb)  G and rs11575837:C > T) and their haplotypes. The prospective observational study was conducted over a 36 mos. follow-up period in a cohort of children (n = 1,515, aged 1.9-40 mos.) residing in a holoendemic P. falciparum transmission region, Siaya, Kenya.ResultsPoisson regression modeling, controlling for anemia-promoting covariates, revealed a significantly increased risk of malaria in carriers of the homozygous mutant allele genotype (TT) for rs11575837 after multiple test correction [Incidence rate ratio (IRR) = 1.540, 95% CI = 1.114-2.129, P = 0.009]. Increased risk of SMA was observed for rs2736191 in children who inherited the CG genotype (IRR = 1.269, 95% CI = 1.009-1.597, P = 0.041) and in the additive model (presence of 1 or 2 copies) (IRR = 1.198, 95% CI = 1.030-1.393, P = 0.019), but was not significant after multiple test correction. Modeling of the haplotypes revealed that the CC haplotype had a significant additive effect for protection against SMA (i.e., reduced risk for development of SMA) after multiple test correction (IRR = 0.823, 95% CI = 0.711-0.952, P = 0.009). Although increased susceptibility to SMA was present in carriers of the GC haplotype (IRR = 1.276, 95% CI = 1.030-1.581, P = 0.026) with an additive effect (IRR = 1.182, 95% CI = 1.018-1.372, P = 0.029), the results did not remain significant after multiple test correction. None of the NCR3 genotypes or haplotypes were associated with all-cause mortality.ConclusionsVariation in NCR3 alters susceptibility to malaria and SMA during the acquisition of naturally-acquired malarial immunity. These results highlight the importance of NK cells in the innate immune response to malaria.

2024-03-04

2024-03-04

https://doi.org/10.1093/pnasnexus/pgad259

2023-08-29

2023-08-29

https://doi.org/10.21203/rs.3.rs-3150748/v1

2023-07-19

2023-07-19

https://europepmc.org/articles/PMC10352311

BackgroundBirth defects are functional and structural abnormalities that impact about 1 in 33 births in the United States. They have been attributed to genetic and other factors such as drugs, cosmetics, food, and environmental pollutants during pregnancy, but for most birth defects there are no known causes.MethodsTo further characterize associations between small molecule compounds and their potential to induce specific birth abnormalities, we gathered knowledge from multiple sources to construct a reproductive toxicity Knowledge Graph (ReproTox-KG) with a focus on associations between birth defects, drugs, and genes. Specifically, we gathered data from drug/birth-defect associations from co-mentions in published abstracts, gene/birth-defect associations from genetic studies, drug- and preclinical-compound-induced gene expression changes in cell lines, known drug targets, genetic burden scores for human genes, and placental crossing scores for small molecules.ResultsUsing ReproTox-KG and semi-supervised learning (SSL), we scored >30,000 preclinical small molecules for their potential to cross the placenta and induce birth defects, and identified >500 birth-defect/gene/drug cliques that can be used to explain molecular mechanisms for drug-induced birth defects. The ReproTox-KG can be accessed via a web-based user interface available at https://maayanlab.cloud/reprotox-kg . This site enables users to explore the associations between birth defects, approved and preclinical drugs, and all human genes.ConclusionsReproTox-KG provides a resource for exploring knowledge about the molecular mechanisms of birth defects with the potential of predicting the likelihood of genes and preclinical small molecules to induce birth defects.

2024-03-04

2024-03-04

https://arxiv.org/abs/2303.08269

Positive and Unlabeled (PU) learning is a type of semi-supervised binary classification where the machine learning algorithm differentiates between a set of positive instances (labeled) and a set of both positive and negative instances (unlabeled). PU learning has broad applications in settings where confirmed negatives are unavailable or difficult to obtain, and there is value in discovering positives among the unlabeled (e.g., viable drugs among untested compounds). Most PU learning algorithms make the selected completely at random (SCAR) assumption, namely that positives are selected independently of their features. However, in many real-world applications, such as healthcare, positives are not SCAR (e.g., severe cases are more likely to be diagnosed), leading to a poor estimate of the proportion, $α$, of positives among unlabeled examples and poor model calibration, resulting in an uncertain decision threshold for selecting positives. PU learning algorithms can estimate $α$ or the probability of an individual unlabeled instance being positive or both. We propose two PU learning algorithms to estimate $α$, calculate calibrated probabilities for PU instances, and improve classification metrics: i) PULSCAR (positive unlabeled learning selected completely at random), and ii) PULSNAR (positive unlabeled learning selected not at random). PULSNAR uses a divide-and-conquer approach that creates and solves several SCAR-like sub-problems using PULSCAR. In our experiments, PULSNAR outperformed state-of-the-art approaches on both synthetic and real-world benchmark datasets.

2024-03-04

2024-03-04

https://europepmc.org/articles/PMC9233820

Plasmodium falciparum infections remain among the leading causes of morbidity and mortality in holoendemic transmission areas. Located within region 5q31.1, the colony-stimulating factor 2 gene (CSF2) encodes granulocyte-macrophage colony-stimulating factor (GM-CSF), a hematopoietic growth factor that mediates host immune responses. Since the effect of CSF2 variation on malaria pathogenesis remains unreported, we investigated the impact of two genetic variants in the 5q31.1 gene region flanking CSF2:g-7032 G > A (rs168681:G > A) and CSF2:g.64544T > C (rs246835:T > C) on the rate and timing of malaria and severe malarial anemia (SMA, Hb 

2023-04-14

2023-04-14

https://europepmc.org/articles/PMC9379605

Epidemiological data across the United States show health disparities in COVID-19 infection, hospitalization, and mortality by race/ethnicity. While the association between elevated SARS-CoV-2 viral loads (VLs) (i.e. upper respiratory tract (URT) and peripheral blood (PB)) and increased COVID-19 severity has been reported, data remain largely unavailable for some disproportionately impacted racial/ethnic groups, particularly for American Indian or Alaska Native (AI/AN) populations. As such, we determined the relationship between SARS-CoV-2 VL dynamics and disease severity in a diverse cohort of hospitalized patients. Results presented here are for study participants (n = 94, ages 21-88 years) enrolled in a prospective observational study between May and October 2020 who had SARS-CoV-2 viral clades 20A, C, and G. Based on self-reported race/ethnicity and sample size distribution, the cohort was stratified into two groups: (AI/AN, n = 43) and all other races/ethnicities combined (non-AI/AN, n = 51). SARS-CoV-2 VLs were quantified in the URT and PB on days 0-3, 6, 9, and 14. The strongest predictor of severe COVID-19 in the study population was the mean VL in PB (OR = 3.34; P = 2.00 × 10-4). The AI/AN group had the following: (1) comparable co-morbidities and admission laboratory values, yet more severe COVID-19 (OR = 4.81; P = 0.014); (2) a 2.1 longer duration of hospital stay (P = 0.023); and (3) higher initial and cumulative PB VLs during severe disease (P = 0.025). Moreover, self-reported race/ethnicity as AI/AN was the strongest predictor of elevated PB VLs (β = 1.08; P = 6.00 × 10-4) and detection of SARS-CoV-2 in PB (hazard ratio = 3.58; P = 0.004). The findings presented here suggest a strong relationship between PB VL (magnitude and frequency) and severe COVID-19, particularly for the AI/AN group.

2023-04-14

2023-04-14

https://europepmc.org/articles/PMC8908195

BackgroundOn March 11, 2020, the New Mexico Governor declared a public health emergency in response to the COVID-19 pandemic. The New Mexico medical advisory team contacted University of New Mexico (UNM) faculty to form a team to consolidate growing information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its disease to facilitate New Mexico's pandemic management. Thus, faculty, physicians, staff, graduate students, and medical students created the "UNM Global Health COVID-19 Intelligence Briefing."ObjectiveIn this paper, we sought to (1) share how to create an informative briefing to guide public policy and medical practice and manage information overload with rapidly evolving scientific evidence; (2) determine the qualitative usefulness of the briefing to its readers; and (3) determine the qualitative effect this project has had on virtual medical education.MethodsMicrosoft Teams was used for manual and automated capture of COVID-19 articles and composition of briefings. Multilevel triaging saved impactful articles to be reviewed, and priority was placed on randomized controlled studies, meta-analyses, systematic reviews, practice guidelines, and information on health care and policy response to COVID-19. The finalized briefing was disseminated by email, a listserv, and posted on the UNM digital repository. A survey was sent to readers to determine briefing usefulness and whether it led to policy or medical practice changes. Medical students, unable to partake in direct patient care, proposed to the School of Medicine that involvement in the briefing should count as course credit, which was approved. The maintenance of medical student involvement in the briefings as well as this publication was led by medical students.ResultsAn average of 456 articles were assessed daily. The briefings reached approximately 1000 people by email and listserv directly, with an unknown amount of forwarding. Digital repository tracking showed 5047 downloads across 116 countries as of July 5, 2020. The survey found 108 (95%) of 114 participants gained relevant knowledge, 90 (79%) believed it decreased misinformation, 27 (24%) used the briefing as their primary source of information, and 90 (79%) forwarded it to colleagues. Specific and impactful public policy decisions were informed based on the briefing. Medical students reported that the project allowed them to improve on their scientific literature assessment, stay current on the pandemic, and serve their community.ConclusionsThe COVID-19 briefings succeeded in informing and guiding New Mexico policy and clinical practice. The project received positive feedback from the community and was shown to decrease information burden and misinformation. The virtual platforms allowed for the continuation of medical education. Variability in subject matter expertise was addressed with training, standardized article selection criteria, and collaborative editing led by faculty.

2023-03-24

2023-03-24

https://europepmc.org/articles/PMC8761598

Plasmodium falciparum (Pf) malaria is among the leading causes of childhood morbidity and mortality worldwide. During a natural infection, ingestion of the malarial parasite product, hemozoin (PfHz), by circulating phagocytic cells induces dysregulation in innate immunity and enhances malaria pathogenesis. Treatment of cultured peripheral blood mononuclear cells (PBMCs) from healthy, malaria-naïve donors with physiological concentrations of PfHz can serve as an in vitro model to investigate cellular processes. Although disruptions in host ubiquitination processes are central to the pathogenesis of many diseases, this system remains unexplored in malaria. As such, we investigated the impact of PfHz on the temporal expression patterns of 84 genes involved in ubiquitination processes. Donor PBMCs were cultured in the absence or presence of PfHz for 3-, 9-, and 24 h. Stimulation with PfHz for 3 h did not significantly alter gene expression. Incubation for 9 h, however, elicited significant changes for 6 genes: 4 were down-regulated (FBXO4, NEDD8, UBE2E3, and UBE2W) and 2 were up-regulated (HERC5 and UBE2J1). PfHz treatment for 24 h significantly altered expression for 14 genes: 12 were down-regulated (ANAPC11, BRCC3, CUL4B, FBXO4, MIB1, SKP2, TP53, UBA2, UBA3, UBE2G1, UBE2G2, and WWP1), while 2 were up-regulated (UBE2J1 and UBE2Z). Collectively, these results demonstrate that phagocytosis of PfHz by PBMCs elicits temporal changes in the transcriptional profiles of genes central to host ubiquitination processes. Results presented here suggest that disruptions in ubiquitination may be a previously undiscovered feature of malaria pathogenesis.

2023-03-24

2023-03-24

https://europepmc.org/articles/PMC9039490

Severe malarial anemia (SMA) is a leading cause of childhood morbidity and mortality in holoendemic Plasmodium falciparum transmission regions. To gain enhanced understanding of predisposing factors for SMA, we explored the relationship between complement component 3 (C3) missense mutations [rs2230199 (2307C>G, Arg>Gly102) and rs11569534 (34420G>A, Gly>Asp1224)], malaria, and SMA in a cohort of children (n = 1617 children) over 36 months of follow-up. Variants were selected based on their ability to impart amino acid substitutions that can alter the structure and function of C3. The 2307C>G mutation results in a basic to a polar residue change (Arg to Gly) at position 102 (β-chain) in the macroglobulin-1 (MG1) domain, while 34420G>A elicits a polar to acidic residue change (Gly to Asp) at position 1224 (α-chain) in the thioester-containing domain. After adjusting for multiple comparisons, longitudinal analyses revealed that inheritance of the homozygous mutant (GG) at 2307 enhanced the risk of SMA (RR = 2.142, 95%CI: 1.229-3.735, P = 0.007). The haplotype containing both wild-type alleles (CG) decreased the incident risk ratio of both malaria (RR = 0.897, 95%CI: 0.828-0.972, P = 0.008) and SMA (RR = 0.617, 95%CI: 0.448-0.848, P = 0.003). Malaria incident risk ratio was also reduced in carriers of the GG (Gly102Gly1224) haplotype (RR = 0.941, 95%CI: 0.888-0.997, P = 0.040). Collectively, inheritance of the missense mutations in MG1 and thioester-containing domain influence the longitudinal risk of malaria and SMA in children exposed to intense Plasmodium falciparum transmission.

2023-03-24

2023-03-24

https://doi.org/10.1093/bioinformatics/btab427

MotivationGenome-wide association studies can reveal important genotype-phenotype associations; however, data quality and interpretability issues must be addressed. For drug discovery scientists seeking to prioritize targets based on the available evidence, these issues go beyond the single study.ResultsHere, we describe rational ranking, filtering and interpretation of inferred gene-trait associations and data aggregation across studies by leveraging existing curation and harmonization efforts. Each gene-trait association is evaluated for confidence, with scores derived solely from aggregated statistics, linking a protein-coding gene and phenotype. We propose a method for assessing confidence in gene-trait associations from evidence aggregated across studies, including a bibliometric assessment of scientific consensus based on the iCite relative citation ratio, and meanRank scores, to aggregate multivariate evidence.This method, intended for drug target hypothesis generation, scoring and ranking, has been implemented as an analytical pipeline, available as open source, with public datasets of results, and a web application designed for usability by drug discovery scientists.Availability and implementationWeb application, datasets and source code via https://unmtid-shinyapps.net/tiga/.Supplementary informationSupplementary data are available at Bioinformatics online.

2024-03-04

2024-03-04

https://doi.org/10.2196/24522

Background:
Incomplete suicidality coding in administrative claims data is a known obstacle for observational studies. With most of the negative outcomes missing from the data, it is challenging to assess the evidence on treatment strategies for the prevention of self-harm in bipolar disorder (BD), including pharmacotherapy and psychotherapy. There are conflicting data from studies on the drug-dependent risk of self-harm, and there is major uncertainty regarding the preventive effect of monotherapy and drug combinations.

Objective:
The aim of this study was to compare all commonly used BD pharmacotherapies, as well as psychotherapy for the risk of self-harm, in a large population of commercially insured individuals, using self-harm imputation to overcome the known limitations of this outcome being underrecorded within US electronic health care records.

Methods:
The IBM MarketScan administrative claims database was used to compare self-harm risk in patients with BD following 65 drug regimens and drug-free periods. Probable but uncoded self-harm events were imputed via machine learning, with different probability thresholds examined in a sensitivity analysis. Comparators included lithium, mood-stabilizing anticonvulsants (MSAs), second-generation antipsychotics (SGAs), first-generation antipsychotics (FGAs), and five classes of antidepressants. Cox regression models with time-varying covariates were built for individual treatment regimens and for any pharmacotherapy with or without psychosocial interventions (“psychotherapy”).

Results:
Among 529,359 patients, 1.66% (n=8813 events) had imputed and/or coded self-harm following the exposure of interest. A higher self-harm risk was observed during adolescence. After multiple testing adjustment (P≤.012), the following six regimens had higher risk of self-harm than lithium: tri/tetracyclic antidepressants + SGA, FGA + MSA, FGA, serotonin-norepinephrine reuptake inhibitor (SNRI) + SGA, lithium + MSA, and lithium + SGA (hazard ratios [HRs] 1.44-2.29), and the following nine had lower risk: lamotrigine, valproate, risperidone, aripiprazole, SNRI, selective serotonin reuptake inhibitor (SSRI), “no drug,” bupropion, and bupropion + SSRI (HRs 0.28-0.74). Psychotherapy alone (without medication) had a lower self-harm risk than no treatment (HR 0.56, 95% CI 0.52-0.60; P=8.76×10-58). The sensitivity analysis showed that the direction of drug-outcome associations did not change as a function of the self-harm probability threshold.

Conclusions:
Our data support evidence on the effectiveness of antidepressants, MSAs, and psychotherapy for self-harm prevention in BD.

Trial Registration:
ClinicalTrials.gov NCT02893371; https://clinicaltrials.gov/ct2/show/NCT02893371

JMIR Ment Health 2021;8(4):e24522

2021-04-21

2021-04-21

https://europepmc.org/articles/PMC7454687

ObjectiveCoronavirus disease 2019 (COVID-19) poses societal challenges that require expeditious data and knowledge sharing. Though organizational clinical data are abundant, these are largely inaccessible to outside researchers. Statistical, machine learning, and causal analyses are most successful with large-scale data beyond what is available in any given organization. Here, we introduce the National COVID Cohort Collaborative (N3C), an open science community focused on analyzing patient-level data from many centers.Materials and methodsThe Clinical and Translational Science Award Program and scientific community created N3C to overcome technical, regulatory, policy, and governance barriers to sharing and harmonizing individual-level clinical data. We developed solutions to extract, aggregate, and harmonize data across organizations and data models, and created a secure data enclave to enable efficient, transparent, and reproducible collaborative analytics.ResultsOrganized in inclusive workstreams, we created legal agreements and governance for organizations and researchers; data extraction scripts to identify and ingest positive, negative, and possible COVID-19 cases; a data quality assurance and harmonization pipeline to create a single harmonized dataset; population of the secure data enclave with data, machine learning, and statistical analytics tools; dissemination mechanisms; and a synthetic data pilot to democratize data access.ConclusionsThe N3C has demonstrated that a multisite collaborative learning health network can overcome barriers to rapidly build a scalable infrastructure incorporating multiorganizational clinical data for COVID-19 analytics. We expect this effort to save lives by enabling rapid collaboration among clinicians, researchers, and data scientists to identify treatments and specialized care and thereby reduce the immediate and long-term impacts of COVID-19.

2025-09-29

2025-09-29

https://europepmc.org/articles/PMC7834915

BackgroundAngiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) have been postulated to affect susceptibility to COVID-19. Observational studies so far have lacked rigorous ascertainment adjustment and international generalisability. We aimed to determine whether use of ACEIs or ARBs is associated with an increased susceptibility to COVID-19 in patients with hypertension.MethodsIn this international, open science, cohort analysis, we used electronic health records from Spain (Information Systems for Research in Primary Care [SIDIAP]) and the USA (Columbia University Irving Medical Center data warehouse [CUIMC] and Department of Veterans Affairs Observational Medical Outcomes Partnership [VA-OMOP]) to identify patients aged 18 years or older with at least one prescription for ACEIs and ARBs (target cohort) or calcium channel blockers (CCBs) and thiazide or thiazide-like diuretics (THZs; comparator cohort) between Nov 1, 2019, and Jan 31, 2020. Users were defined separately as receiving either monotherapy with these four drug classes, or monotherapy or combination therapy (combination use) with other antihypertensive medications. We assessed four outcomes: COVID-19 diagnosis; hospital admission with COVID-19; hospital admission with pneumonia; and hospital admission with pneumonia, acute respiratory distress syndrome, acute kidney injury, or sepsis. We built large-scale propensity score methods derived through a data-driven approach and negative control experiments across ten pairwise comparisons, with results meta-analysed to generate 1280 study effects. For each study effect, we did negative control outcome experiments using a possible 123 controls identified through a data-rich algorithm. This process used a set of predefined baseline patient characteristics to provide the most accurate prediction of treatment and balance among patient cohorts across characteristics. The study is registered with the EU Post-Authorisation Studies register, EUPAS35296.FindingsAmong 1 355 349 antihypertensive users (363 785 ACEI or ARB monotherapy users, 248 915 CCB or THZ monotherapy users, 711 799 ACEI or ARB combination users, and 473 076 CCB or THZ combination users) included in analyses, no association was observed between COVID-19 diagnosis and exposure to ACEI or ARB monotherapy versus CCB or THZ monotherapy (calibrated hazard ratio [HR] 0·98, 95% CI 0·84-1·14) or combination use exposure (1·01, 0·90-1·15). ACEIs alone similarly showed no relative risk difference when compared with CCB or THZ monotherapy (HR 0·91, 95% CI 0·68-1·21; with heterogeneity of >40%) or combination use (0·95, 0·83-1·07). Directly comparing ACEIs with ARBs demonstrated a moderately lower risk with ACEIs, which was significant with combination use (HR 0·88, 95% CI 0·79-0·99) and non-significant for monotherapy (0·85, 0·69-1·05). We observed no significant difference between drug classes for risk of hospital admission with COVID-19, hospital admission with pneumonia, or hospital admission with pneumonia, acute respiratory distress syndrome, acute kidney injury, or sepsis across all comparisons.InterpretationNo clinically significant increased risk of COVID-19 diagnosis or hospital admission-related outcomes associated with ACEI or ARB use was observed, suggesting users should not discontinue or change their treatment to decrease their risk of COVID-19.FundingWellcome Trust, UK National Institute for Health Research, US National Institutes of Health, US Department of Veterans Affairs, Janssen Research & Development, IQVIA, South Korean Ministry of Health and Welfare Republic, Australian National Health and Medical Research Council, and European Health Data and Evidence Network.

2021-03-03

2021-03-03

https://europepmc.org/articles/PMC7442425

BackgroundHydroxychloroquine, a drug commonly used in the treatment of rheumatoid arthritis, has received much negative publicity for adverse events associated with its authorisation for emergency use to treat patients with COVID-19 pneumonia. We studied the safety of hydroxychloroquine, alone and in combination with azithromycin, to determine the risk associated with its use in routine care in patients with rheumatoid arthritis.MethodsIn this multinational, retrospective study, new user cohort studies in patients with rheumatoid arthritis aged 18 years or older and initiating hydroxychloroquine were compared with those initiating sulfasalazine and followed up over 30 days, with 16 severe adverse events studied. Self-controlled case series were done to further establish safety in wider populations, and included all users of hydroxychloroquine regardless of rheumatoid arthritis status or indication. Separately, severe adverse events associated with hydroxychloroquine plus azithromycin (compared with hydroxychloroquine plus amoxicillin) were studied. Data comprised 14 sources of claims data or electronic medical records from Germany, Japan, the Netherlands, Spain, the UK, and the USA. Propensity score stratification and calibration using negative control outcomes were used to address confounding. Cox models were fitted to estimate calibrated hazard ratios (HRs) according to drug use. Estimates were pooled where the I 2 value was less than 0·4.FindingsThe study included 956 374 users of hydroxychloroquine, 310 350 users of sulfasalazine, 323 122 users of hydroxychloroquine plus azithromycin, and 351 956 users of hydroxychloroquine plus amoxicillin. No excess risk of severe adverse events was identified when 30-day hydroxychloroquine and sulfasalazine use were compared. Self-controlled case series confirmed these findings. However, long-term use of hydroxychloroquine appeared to be associated with increased cardiovascular mortality (calibrated HR 1·65 [95% CI 1·12-2·44]). Addition of azithromycin appeared to be associated with an increased risk of 30-day cardiovascular mortality (calibrated HR 2·19 [95% CI 1·22-3·95]), chest pain or angina (1·15 [1·05-1·26]), and heart failure (1·22 [1·02-1·45]).InterpretationHydroxychloroquine treatment appears to have no increased risk in the short term among patients with rheumatoid arthritis, but in the long term it appears to be associated with excess cardiovascular mortality. The addition of azithromycin increases the risk of heart failure and cardiovascular mortality even in the short term. We call for careful consideration of the benefit-risk trade-off when counselling those on hydroxychloroquine treatment.FundingNational Institute for Health Research (NIHR) Oxford Biomedical Research Centre, NIHR Senior Research Fellowship programme, US National Institutes of Health, US Department of Veterans Affairs, Janssen Research and Development, IQVIA, Korea Health Industry Development Institute through the Ministry of Health and Welfare Republic of Korea, Versus Arthritis, UK Medical Research Council Doctoral Training Partnership, Foundation Alfonso Martin Escudero, Innovation Fund Denmark, Novo Nordisk Foundation, Singapore Ministry of Health's National Medical Research Council Open Fund Large Collaborative Grant, VINCI, Innovative Medicines Initiative 2 Joint Undertaking, EU's Horizon 2020 research and innovation programme, and European Federation of Pharmaceutical Industries and Associations.

2021-03-03

2021-03-03

https://europepmc.org/articles/PMC7338498

Alendronate and raloxifene are among the most popular anti-osteoporosis medications. However, there is a lack of head-to-head comparative effectiveness studies comparing the two treatments. We conducted a retrospective large-scale multicenter study encompassing over 300 million patients across nine databases encoded in the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). The primary outcome was the incidence of osteoporotic hip fracture, while secondary outcomes were vertebral fracture, atypical femoral fracture (AFF), osteonecrosis of the jaw (ONJ), and esophageal cancer. We used propensity score trimming and stratification based on an expansive propensity score model with all pre-treatment patient characteritistcs. We accounted for unmeasured confounding using negative control outcomes to estimate and adjust for residual systematic bias in each data source. We identified 283,586 alendronate patients and 40,463 raloxifene patients. There were 7.48 hip fracture, 8.18 vertebral fracture, 1.14 AFF, 0.21 esophageal cancer and 0.09 ONJ events per 1,000 person-years in the alendronate cohort and 6.62, 7.36, 0.69, 0.22 and 0.06 events per 1,000 person-years, respectively, in the raloxifene cohort. Alendronate and raloxifene have a similar hip fracture risk (hazard ratio [HR] 1.03, 95% confidence interval [CI] 0.94-1.13), but alendronate users are more likely to have vertebral fractures (HR 1.07, 95% CI 1.01-1.14). Alendronate has higher risk for AFF (HR 1.51, 95% CI 1.23-1.84) but similar risk for esophageal cancer (HR 0.95, 95% CI 0.53-1.70), and ONJ (HR 1.62, 95% CI 0.78-3.34). We demonstrated substantial control of measured confounding by propensity score adjustment, and minimal residual systematic bias through negative control experiments, lending credibility to our effect estimates. Raloxifene is as effective as alendronate and may remain an option in the prevention of osteoporotic fracture.

2021-03-03

2021-03-03

https://doi.org/10.1038/s10038-019-0692-3

2019-10-30

2022-05-29

https://doi.org/10.1093/jamia/ocz173

2019-10-25

2022-05-29

2021-03-03

2022-05-31

https://doi.org/10.1016/j.psyneuen.2019.104511

OBJECTIVE:To compare the largest set of bipolar disorder pharmacotherapies to date (102 drugs and drug combinations) for risk of diabetes mellitus (DM). METHODS:The IBM MarketScan® database was used to retrospectively analyze data on 565,253 adults with bipolar disorder without prior glucose metabolism-related diagnoses. The pharmacotherapies compared were lithium, mood-stabilizing anticonvulsants, antipsychotics, and antidepressants (monotherapy and multi-class polypharmacy). Cox regression modeling included fixed pre-treatment covariates and time-varying drug exposure covariates to estimate the hazard ratio (HR) of each treatment versus "No drug". RESULTS:The annual incidence of new-onset diabetes during the exposure period was 3.09 % (22,951 patients). The HR of drug-dependent DM ranged from 0.79 to 2.37. One-third of the studied pharmacotherapies, including most of the antipsychotic-containing regimens, had a significantly higher risk of DM compared to "No drug". A significantly lower DM risk was associated with lithium, lamotrigine, oxcarbazepine and bupropion monotherapies, selective serotonin reuptake inhibitors (SSRI) mono-class therapy and several drug combinations containing bupropion and an SSRI. As additional drugs were combined in more complex polypharmacy, higher HRs were consistently observed. CONCLUSIONS:There is an increased risk of diabetes mellitus associated with antipsychotic and psychotropic polypharmacy use in bipolar disorder. The evidence of a lower-than-baseline risk of DM with lamotrigine, oxcarbazepine, lithium, and bupropion monotherapy should be further investigated.

2019-12-18

2019-12-18

http://europepmc.org/articles/PMC6698010

BACKGROUND:Severe malarial anemia (SMA) is a leading cause of malaria-related morbidity and mortality in children. The genetic factors that influence development of SMA and inefficient erythropoiesis, a central pathogenic feature of SMA, are only partially understood. METHODS:We performed a pilot Genome-wide Association Study (GWAS) on children with Plasmodium falciparum. The GWAS was performed using the Illumina® Infinium® HD Super Assay in conjunction with Illumina's® Human Omni2.5-8v1 BeadChip (with > 2.45 M markers). Data were analyzed using single SNP logistic regression analysis with an additive model of inheritance controlling for covariates. Results from our pilot global genomics study identified that variation in interleukin (IL)-7 was associated with enhanced risk of SMA. To validate this finding, we investigated the relationship between genotypes and/or haplotypes of two single nucleotide polymorphisms (SNPs) in IL7 [72194 T/C and - 2440 A/G] and susceptibility to both SMA and inefficient erythropoiesis [i.e., reticulocyte production index (RPI)

2019-09-26

2019-09-26

http://europepmc.org/articles/PMC6642287

BACKGROUND:Severe malarial anaemia (SMA) is a leading cause of childhood mortality in holoendemic Plasmodium falciparum regions. METHODS:To gain an improved understanding of SMA pathogenesis, whole genome and transcriptome profiling was performed in Kenyan children (n=144, 3-36months) with discrete non-SMA and SMA phenotypes. Leukocyte associated immunoglobulin like receptor 1 (LAIR1) emerged as a predictor of susceptibility to SMA (PA); rs2287827 (18835G>A)] and clinical outcomes were investigated in individuals (n=1512,

2019-09-26

2019-09-26

http://europepmc.org/articles/PMC6642411

BACKGROUND:Leukocyte-associated immunoglobulin like receptor-1 (LAIR1) is a transmembrane inhibitory receptor that influences susceptibility to a myriad of inflammatory diseases. Our recent investigations of severe malarial anaemia (SMA) pathogenesis in Kenyan children discovered that novel LAIR1 genetic variants which were associated with decreased LAIR1 transcripts enhanced the longitudinal risk of SMA and all-cause mortality. METHODS:To characterize the molecular mechanism(s) responsible for altered LAIR1 signalling in severe malaria, we determined LAIR1 transcripts and protein, sLAIR1, sLAIR2, and complement component 1q (C1q) in children with malarial anaemia, followed by a series of in vitro experiments investigating the LAIR1 signalling cascade. FINDINGS:Kenyan children with SMA had elevated circulating levels of soluble LAIR1 (sLAIR1) relative to non-SMA (1.69-fold P 

2019-09-26

2019-09-26

http://europepmc.org/articles/PMC6614999

BACKGROUND:Patient education has taken center stage in successfully shared decision making between patients and health care providers. However, little is known about how patients with bipolar disorder typically obtain information on their illness and the treatment options available to them. OBJECTIVE:This study aimed to obtain the perspectives of patients with bipolar disorder and their family members on the preferred and most effectively used information channels on bipolar disorder and the available treatment options. METHODS:We conducted nine focus groups in Montana, New Mexico, and California, in which we surveyed 84 individuals including patients with bipolar disorder and family members of patients with bipolar disorder. The participants were recruited using National Alliance on Mental Illness mailing lists and websites. Written verbatim responses to semistructured questionnaires were analyzed using summative content analysis based on grounded theory. Two annotators coded and analyzed the data on the sentence or phrase level to create themes. Relationships between demographics and information channel were also examined using the Chi-square and Fisher exact tests. RESULTS:The focus group participants mentioned a broad range of information channels that were successfully used in the past and could be recommended for future information dissemination. The majority of participants used providers (74%) and internet-based resources (75%) as their main information sources. There was no association between internet use and basic demographics such as age or geographical region of the focus groups. Patients considered time constraints and the fast pace in which an overwhelming amount of information is often presented by the provider as major barriers to successful provider-patient interactions. If Web-based channels were used, the participants perceived information obtained through Web-based channels as more helpful than information received in the provider's office (P

2019-09-26

2019-09-26

https://doi.org/10.1016/j.jad.2019.04.009

BACKGROUND:This study compared the largest set of bipolar disorder pharmacotherapies to date (71 drugs and drug combinations) for risk of kidney disorders (KDs). METHODS:This retrospective observational study used the IBM MarketScan® database to analyze data on 591,052 adults with bipolar disorder without prior nephropathy, for onset of KDs (of "moderate" or "high" severity) following psychopharmacotherapy (lithium, mood stabilizing anticonvulsants [MSAs], antipsychotics, antidepressants), or "No drug". Cox regression models included fixed pre-treatment covariates and time-varying drug exposure covariates to estimate the hazard ratio (HR) of each treatment versus "No drug". RESULTS:Newly observed KD occurred in 14,713 patients. No regimen had significantly lower risk of KDs than "No drug". The HR estimates ranged 0.86-2.66 for "all" KDs and 0.87-5.30 for "severe" KDs. As additional drugs were combined to compare more complex polypharmacies, higher HRs were consistently observed. Most regimens containing lithium, MSAs, or antipsychotics had a higher risk than "No drug" (p 

2019-09-26

2019-09-26

https://doi.org/10.1016/j.ajog.2018.07.003

BACKGROUND:The opioid epidemic in the United States is a public health emergency. Minimally invasive surgical technology has decreased length of hospital stay, improved postoperative recovery, and decreased postoperative pain. Hysterectomy is one of the most commonly performed surgeries in the United States. Increasing trends in minimally invasive gynecologic surgery are expected to reduce patients' postoperative pain. It is unclear whether this assumption has resulted in decreasing postoperative opioid prescriptions or patient need for these prescriptions, as prescribing patterns may be contributing to the current opioid public health emergency. OBJECTIVE:We sought to describe opioid prescribing and patient procurement practices for postoperative pain at time of discharge for benign hysterectomy from 2004 through 2014 using the Truven Health Analytics MarketScan Research Database. The trends of the route of hysterectomy over this time period were concomitantly described to reflect the movement toward more minimally invasive approaches. STUDY DESIGN:The Truven Health Analytics MarketScan Research Database including the Commercial Claims and Encounters Database, and the Medicare Supplemental and Coordination of Benefits Database were utilized. Current Procedural Terminology, 4th Edition, and International Classification of Diseases, Ninth Revision, codes identified all patients who underwent a hysterectomy for benign indications from 2004 through 2014. Hysterectomy routes were categorized into abdominal, laparoscopic, and vaginal. The MarketScan database captures prescriptions filled at a retail or mail-order pharmacy and does not capture prescriptions filled within the inpatient, hospital facility. The days of opioids procured by patients at the time of discharge were identified for each encounter. Descriptive statistics were used to summarize data within the entire study period. Although this article is purely descriptive, further analyses were conducted for exploratory purposes only. analysis of variance and χ2 analyses were used for continuous and categorical variables, respectively. Multiple linear regression models were used to describe associations between variables of interest and postoperative opioid prescriptions. RESULTS:We identified 793,016 patients who underwent a hysterectomy for benign indications from 2004 through 2014. Of these, 96% were identified from the Commercial Claims and Encounters Database. During the study period, the overall route of hysterectomy was categorized into 40.5% abdominal, 42.0% laparoscopic, and 17.5% vaginal hysterectomy. The route of hysterectomy changed from 60.2-25.6% (a decrease of Δ = 34.58; 95% confidence interval, 33.96-35.20) for abdominal, 17.0-61.9% (an increase of Δ = 44.83; 95% confidence interval, 44.21-45.44) for laparoscopic, and 22.8-12.6% (a decrease of Δ = 10.25; 95% confidence interval, 9.77-10.73) for vaginal. At discharge, the percentage of patients who were prescribed opioids and filled them increased from 25.6-82.1% (an increase of Δ = 56.50; 95% confidence interval, 55.88-57.13 with P < .001) from 2004 through 2014 for all hysterectomy routes. Additionally, the quantity of opioids prescribed also increased. CONCLUSION:Opioid prescriptions filled for postoperative pain after hysterectomy substantially increased from 2004 through 2014. Opioid prescription procurement has increased despite a concomitant increase in minimally invasive hysterectomy routes. In light of the current opioid epidemic, physicians must recognize that postoperative prescribing practices may contribute to chronic opioid use. Heightened awareness of opioid prescribing practices following surgery is critically important to decrease risk of development of chronic opioid dependence.

2019-09-26

2019-09-26

http://europepmc.org/articles/PMC6586061

OBJECTIVES:This study compared 29 drugs for risk of psychiatric hospitalization in bipolar disorders, addressing the evidence gap on the >50 drugs used by US patients for treatment. METHODS:The Truven Health Analytics MarketScan® database was used to identify 190 894 individuals with bipolar or schizoaffective disorder who filled a prescription for one of 29 drugs of interest: lithium, first- or second-generation antipsychotics, mood-stabilizing anticonvulsants, and antidepressants. Competing risks regression survival analysis was used to compare drugs for risk of psychiatric hospitalization, adjusting for patient age, sex, comorbidities, and pretreatment medications. Other competing risks were ending monotherapy and non-psychiatric hospitalization. RESULTS:Three drugs were associated with significantly lower risk of psychiatric hospitalization than lithium: valproate (relative risk [RR] = 0.80, P = 3.20 × 10-4 ), aripiprazole (RR = 0.80, P = 3.50 × 10-4 ), and bupropion (RR = 0.80, P = 2.80 × 10-4 ). Eight drugs were associated with significantly higher risk of psychiatric hospitalization: haloperidol (RR = 1.57, P = 9.40 × 10-4 ), clozapine (RR = 1.52, P = .017), fluoxetine (RR = 1.17, P = 3.70 × 10-3 ), sertraline (RR = 1.17, P = 3.20 × 10-3 ), citalopram (RR = 1.14, P = .013), duloxetine (RR = 1.24, P = 5.10 × 10-4 ), venlafaxine (RR = 1.33; P = 1.00 × 10-6 ), and ziprasidone (RR = 1.25; P = 6.20 × 10-3 ). CONCLUSIONS:This largest reported retrospective observational study on bipolar disorders pharmacotherapy to date demonstrates that the majority of patients end monotherapy within 2 months after treatment start. The risk of psychiatric hospitalization varied almost two-fold across individual medications. The data add to the evidence favoring lithium and mood stabilizer use in short-term bipolar disorder management. The findings that the dopaminergic drugs aripiprazole and bupropion had better outcomes than other members of their respective classes and that antidepressant outcomes may vary by baseline mood polarity merit further investigation.

2019-09-26

2019-09-26

2021-03-03

2022-05-31

2021-03-03

2022-05-31

2021-03-03

2021-03-03

2021-03-03

2022-05-31

http://europepmc.org/articles/PMC5763323

As part of a series of Patient-Centered Outcomes Research Institute-funded large-scale retrospective observational studies on bipolar disorder (BD) treatments and outcomes, we sought the input of patients with BD and their family members to develop research questions. We aimed to identify systemic root causes of patient-reported challenges with BD management in order to guide subsequent studies and initiatives.Three focus groups were conducted where patients and their family members (total n = 34) formulated questions around the central theme, "What do you wish you had known in advance or over the course of treatment for BD?" In an affinity mapping exercise, participants clustered their questions and ranked the resulting categories by importance. The research team and members of our patient partner advisory council further rated the questions by expected impact on patients. Using a Theory of Constraints systems thinking approach, several causal models of BD management challenges and their potential solution were developed with patients using the focus group data.A total of 369 research questions were mapped to 33 categories revealing 10 broad themes. The top priorities for patient stakeholders involved pharmacotherapy and treatment alternatives. Analysis of causal relationships underlying 47 patient concerns revealed two core conflicts: for patients, whether or not to take pharmacotherapy, and for mental health services, the dilemma of care quality vs quantity.To alleviate the core conflicts identified, BD management requires a coordinated multidisciplinary approach including: improved access to mental health services, objective diagnostics, sufficient provider visit time, evidence-based individualized treatment, and psychosocial support.

2019-09-26

2019-09-26

http://europepmc.org/articles/PMC5346028

Chromosomal microarray analysis (CMA) is recognized as the first-tier test in the genetic evaluation of children with developmental delays, intellectual disabilities, congenital anomalies and autism spectrum disorders of unknown etiology.To optimize detection of clinically relevant copy number variants associated with these conditions, we designed a whole-genome microarray, FirstStepDx PLUS (FSDX). A set of 88,435 custom probes was added to the Affymetrix CytoScanHD platform targeting genomic regions strongly associated with these conditions. This combination of 2,784,985 total probes results in the highest probe coverage and clinical yield for these disorders.Clinical testing of this patient population is validated on DNA from either non-invasive buccal swabs or traditional blood samples. In this report we provide data demonstrating the analytic and clinical validity of FSDX and provide an overview of results from the first 7,570 consecutive patients tested clinically. We further demonstrate that buccal sampling is an effective method of obtaining DNA samples, which may provide improved results compared to traditional blood sampling for patients with neurodevelopmental disorders who exhibit somatic mosaicism.

2019-09-26

2019-09-26

http://europepmc.org/articles/PMC4936996

Bipolar disorder refers to a group of chronic psychiatric disorders of mood and energy levels. While dramatic psychiatric symptoms dominate the acute phase of the diseases, the chronic course is often determined by an increasing burden of co-occurring medical conditions. High rates of diabetes mellitus in patients with bipolar disorder are particularly striking, yet unexplained. Treatment and lifestyle factors could play a significant role, and some studies also suggest shared pathophysiology and risk factors.In this systematic literature review, we explored data around the relationship between bipolar disorder and diabetes mellitus in recently published population-based cohort studies with special focus on the elderly.A systematic search in the PubMed database for the combined terms "bipolar disorder" AND "elderly" AND "diabetes" in papers published between January 2009 and December 2015 revealed 117 publications; 7 studies were large cohort studies, and therefore, were included in our review.We found that age- and gender- adjusted risk for diabetes mellitus was increased in patients with bipolar disorder and vice versa (odds ratio range between 1.7 and 3.2).Our results in large population-based cohort studies are consistent with the results of smaller studies and chart reviews. Even though it is likely that heterogeneous risk factors may play a role in diabetes mellitus and in bipolar disorder, growing evidence from cell culture experiments and animal studies suggests shared disease mechanisms. Furthermore, disease-modifying effects of bipolar disorder and diabetes mellitus on each other appear to be substantial, impacting both treatment response and outcomes.The risk of diabetes mellitus in patients with bipolar disorder is increased. Our findings add to the growing literature on this topic. Increasing evidence for shared disease mechanisms suggests new disease models that could explain the results of our study. A better understanding of the complex relationship between bipolar disorder and diabetes mellitus could lead to novel therapeutic approaches and improved outcomes.

2019-09-26

2019-09-26

http://europepmc.org/articles/PMC5089566

Thyroid abnormalities in patients with bipolar disorder (BD) have been linked to lithium treatment for decades, yet other drugs have been less well studied. Our objective was to compare hypothyroidism risk for lithium versus the anticonvulsants and second-generation antipsychotics commonly prescribed for BD.Administrative claims data on 24,574 patients with BD were analyzed with competing risk survival analysis. Inclusion criteria were (i) one year of no prior hypothyroid diagnosis nor BD drug treatment, (ii) followed by at least one thyroid test during BD monotherapy on lithium carbonate, mood-stabilizing anticonvulsants (lamotrigine, valproate, oxcarbazepine, or carbamazepine) or antipsychotics (aripiprazole, olanzapine, risperidone, or quetiapine). The outcome was cumulative incidence of hypothyroidism per drug, in the presence of the competing risk of ending monotherapy, adjusted for age, sex, physician visits, and thyroid tests.Adjusting for covariates, the four-year cumulative risk of hypothyroidism for lithium (8.8%) was 1.39-fold that of the lowest risk therapy, oxcarbazepine (6.3%). Lithium was non-statistically significantly different from quetiapine. While lithium conferred a higher risk when compared to all other treatments combined as a group, hypothyroidism risk error bars overlapped for all drugs. Treatment (p = 3.86e-3), age (p = 6.91e-10), sex (p = 3.93e-7), and thyroid testing (p = 2.79e-87) affected risk. Patients taking lithium were tested for hypothyroidism 2.26-3.05 times more frequently than those on other treatments.Thyroid abnormalities occur frequently in patients with BD regardless of treatment. Therefore, patients should be regularly tested for clinical or subclinical thyroid abnormalities on all therapies and treated as indicated to prevent adverse effects of hormone imbalances on mood.

2019-09-26

2019-09-26

http://europepmc.org/articles/PMC4819617

BACKGROUND:Wolf-Hirschhorn syndrome (WHS) is a contiguous gene deletion syndrome involving variable size deletions of the 4p16.3 region. Seizures are frequently, but not always, associated with WHS. We hypothesised that the size and location of the deleted region may correlate with seizure presentation. METHODS:Using chromosomal microarray analysis, we finely mapped the breakpoints of copy number variants (CNVs) in 48 individuals with WHS. Seizure phenotype data were collected through parent-reported answers to a comprehensive questionnaire and supplemented with available medical records. RESULTS:We observed a significant correlation between the presence of an interstitial 4p deletion and lack of a seizure phenotype (Fisher's exact test p=3.59e-6). In our cohort, there were five individuals with interstitial deletions with a distal breakpoint at least 751 kbp proximal to the 4p terminus. Four of these individuals have never had an observable seizure, and the fifth individual had a single febrile seizure at the age of 1.5 years. All other individuals in our cohort whose deletions encompass the terminal 751 kbp region report having seizures typical of WHS. Additional examples from the literature corroborate these observations and further refine the candidate seizure susceptibility region to a region 197 kbp in size, starting 368 kbp from the terminus of chromosome 4. CONCLUSIONS:We identify a small terminal region of chromosome 4p that represents a seizure susceptibility region. Deletion of this region in the context of WHS is sufficient for seizure occurrence.

2019-09-26

2019-09-26

http://europepmc.org/articles/PMC4134480

The entire drug safety enterprise has a need to search, retrieve, evaluate, and synthesize scientific evidence more efficiently. This discovery and synthesis process would be greatly accelerated through access to a common framework that brings all relevant information sources together within a standardized structure. This presents an opportunity to establish an open-source community effort to develop a global knowledge base, one that brings together and standardizes all available information for all drugs and all health outcomes of interest (HOIs) from all electronic sources pertinent to drug safety. To make this vision a reality, we have established a workgroup within the Observational Health Data Sciences and Informatics (OHDSI, http://ohdsi.org) collaborative. The workgroup's mission is to develop an open-source standardized knowledge base for the effects of medical products and an efficient procedure for maintaining and expanding it. The knowledge base will make it simpler for practitioners to access, retrieve, and synthesize evidence so that they can reach a rigorous and accurate assessment of causal relationships between a given drug and HOI. Development of the knowledge base will proceed with the measureable goal of supporting an efficient and thorough evidence-based assessment of the effects of 1,000 active ingredients across 100 HOIs. This non-trivial task will result in a high-quality and generally applicable drug safety knowledge base. It will also yield a reference standard of drug-HOI pairs that will enable more advanced methodological research that empirically evaluates the performance of drug safety analysis methods.

2019-09-26

2019-09-26

http://europepmc.org/articles/PMC4098669

Genetics clearly plays a major role in the etiology of autism spectrum disorders (ASDs), but studies to date are only beginning to characterize the causal genetic variants responsible. Until recently, studies using multiple extended multi-generation families to identify ASD risk genes had not been undertaken.We identified haplotypes shared among individuals with ASDs in large multiplex families, followed by targeted DNA capture and sequencing to identify potential causal variants. We also assayed the prevalence of the identified variants in a large ASD case/control population.We identified 584 non-conservative missense, nonsense, frameshift and splice site variants that might predispose to autism in our high-risk families. Eleven of these variants were observed to have odds ratios greater than 1.5 in a set of 1,541 unrelated children with autism and 5,785 controls. Three variants, in the RAB11FIP5, ABP1, and JMJD7-PLA2G4B genes, each were observed in a single case and not in any controls. These variants also were not seen in public sequence databases, suggesting that they may be rare causal ASD variants. Twenty-eight additional rare variants were observed only in high-risk ASD families. Collectively, these 39 variants identify 36 genes as ASD risk genes. Segregation of sequence variants and of copy number variants previously detected in these families reveals a complex pattern, with only a RAB11FIP5 variant segregating to all affected individuals in one two-generation pedigree. Some affected individuals were found to have multiple potential risk alleles, including sequence variants and copy number variants (CNVs), suggesting that the high incidence of autism in these families could be best explained by variants at multiple loci.Our study is the first to use haplotype sharing to identify familial ASD risk loci. In total, we identified 39 variants in 36 genes that may confer a genetic risk of developing autism. The observation of 11 of these variants in unrelated ASD cases further supports their role as ASD risk variants.

2019-09-26

2019-09-26

http://europepmc.org/articles/PMC3544904

Structural variation is thought to play a major etiological role in the development of autism spectrum disorders (ASDs), and numerous studies documenting the relevance of copy number variants (CNVs) in ASD have been published since 2006. To determine if large ASD families harbor high-impact CNVs that may have broader impact in the general ASD population, we used the Affymetrix genome-wide human SNP array 6.0 to identify 153 putative autism-specific CNVs present in 55 individuals with ASD from 9 multiplex ASD pedigrees. To evaluate the actual prevalence of these CNVs as well as 185 CNVs reportedly associated with ASD from published studies many of which are insufficiently powered, we designed a custom Illumina array and used it to interrogate these CNVs in 3,000 ASD cases and 6,000 controls. Additional single nucleotide variants (SNVs) on the array identified 25 CNVs that we did not detect in our family studies at the standard SNP array resolution. After molecular validation, our results demonstrated that 15 CNVs identified in high-risk ASD families also were found in two or more ASD cases with odds ratios greater than 2.0, strengthening their support as ASD risk variants. In addition, of the 25 CNVs identified using SNV probes on our custom array, 9 also had odds ratios greater than 2.0, suggesting that these CNVs also are ASD risk variants. Eighteen of the validated CNVs have not been reported previously in individuals with ASD and three have only been observed once. Finally, we confirmed the association of 31 of 185 published ASD-associated CNVs in our dataset with odds ratios greater than 2.0, suggesting they may be of clinical relevance in the evaluation of children with ASDs. Taken together, these data provide strong support for the existence and application of high-impact CNVs in the clinical genetic evaluation of children with ASD.

2019-09-26

2019-09-26

http://europepmc.org/articles/PMC3436888

During the last several years, high-density genotyping SNP arrays have facilitated genome-wide association studies (GWAS) that successfully identified common genetic variants associated with a variety of phenotypes. However, each of the identified genetic variants only explains a very small fraction of the underlying genetic contribution to the studied phenotypic trait. Moreover, discordance observed in results between independent GWAS indicates the potential for Type I and II errors. High reliability of genotyping technology is needed to have confidence in using SNP data and interpreting GWAS results. Therefore, reproducibility of two widely genotyping technology platforms from Affymetrix and Illumina was assessed by analyzing four technical replicates from each of the six individuals in five laboratories. Genotype concordance of 99.40% to 99.87% within a laboratory for the sample platform, 98.59% to 99.86% across laboratories for the same platform, and 98.80% across genotyping platforms was observed. Moreover, arrays with low quality data were detected when comparing genotyping data from technical replicates, but they could not be detected according to venders' quality control (QC) suggestions. Our results demonstrated the technical reliability of currently available genotyping platforms but also indicated the importance of incorporating some technical replicates for genotyping QC in order to improve the reliability of GWAS results. The impact of discordant genotypes on association analysis results was simulated and could explain, at least in part, the irreproducibility of some GWAS findings when the effect size (i.e. the odds ratio) and the minor allele frequencies are low.

2019-09-26

2019-09-26

http://europepmc.org/articles/PMC3297828

Many public and private genome-wide association studies that we have analyzed include flaws in design, with avoidable confounding appearing as a norm rather than the exception. Rather than recognizing flawed research design and addressing that, a category of quality-control statistical methods has arisen to treat only the symptoms. Reflecting more deeply, we examine elements of current genomic research in light of the traditional scientific method and find that hypotheses are often detached from data collection, experimental design, and causal theories. Association studies independent of causal theories, along with multiple testing errors, too often drive health care and public policy decisions. In an era of large-scale biological research, we ask questions about the role of statistical analyses in advancing coherent theories of diseases and their mechanisms. We advocate for reinterpretation of the scientific method in the context of large-scale data analysis opportunities and for renewed appreciation of falsifiable hypotheses, so that we can learn more from our best mistakes.

2019-09-26

2019-09-26

http://europepmc.org/articles/PMC3244396

Bipolar disorder is a severe psychiatric disorder with high heritability. Co-morbid conditions are common and might define latent subgroups of patients that are more homogeneous with respect to genetic risk factors.In the Caucasian GAIN bipolar disorder sample of 1000 cases and 1034 controls, we tested the association of single nucleotide polymorphisms with patient subgroups defined by co-morbidity.Bipolar disorder with psychosis and/or substance abuse in the absence of alcohol dependence was associated with the rare variant rs1039002 in the vicinity of the gene phosphodiesterase 10A (PDE10A) on chromosome 6q27 (p = 1.7×10⁻⁸). PDE10A has been implicated in the pathophysiology of psychosis. Antagonists to the encoded protein are currently in clinical testing. Another rare variant, rs12563333 (p = 5.9×10⁻⁸) on chromosome 1q41 close to the MAP/microtubule affinity-regulating kinase 1 (MARK1) gene, approached the genome-wide level of significance in this subgroup. Homozygotes for the minor allele were present in cases and absent in controls. Bipolar disorder with alcohol dependence and other co-morbidities was associated with SNP rs2727943 (p = 3.3×10⁻⁸) on chromosome 3p26.3 located between the genes contactin-4 precursor (BIG-2) and contactin 6 (CNTN6). All three associations were found under the recessive genetic model. Bipolar disorder with low probability of co-morbid conditions did not show significant associations.Conceptualizing bipolar disorder as a heterogeneous disorder with regard to co-morbid conditions might facilitate the identification of genetic risk alleles. Rare variants might contribute to the susceptibility to bipolar disorder.

2019-09-26

2019-09-26

http://europepmc.org/articles/PMC3287937

To enable the assessment of compound heterozygosity, we propose a simple approach for incorporating genotype phase in a rare variant collapsing procedure for the analysis of DNA sequence data. When multiple variants are identified within a gene, knowing the phase of each variant may provide additional statistical power to detect associations with phenotypes that follow a recessive or additive inheritance pattern. We begin by phasing all marker data; then, we collapse nonsynonymous single-nucleotide polymorphisms within genes on each phased haplotype, resulting in a single diploid genotype for each gene, which represents whether one or both haplotypes carry a nonsynonymous variant allele. A recessive or additive association test can then be used to assess the relationship between the collapsed genotype and the phenotype of interest. We apply this approach to the unrelated individuals data from Genetic Analysis Workshop 17 and compare the results of the additive test with a dominant test in which phase is not informative. Analysis of the first phenotype replicate shows that the FLT1 gene is significantly associated with both Q1 and the binary affection status phenotype. This association was detected by both the additive and dominant tests, although the additive phase-informed test resulted in a smaller p-value. No false-positive results were detected in the first phenotype replicate. Analysis of the average values of all phenotype replicates correctly identified five other genes important to the simulation, but with an increase in false-positive rates. The accuracy of our method is contingent on correct phase determination.

2019-09-26

2019-09-26

https://doi.org/10.1038/tpj.2010.27

The robustness of genome-wide association study (GWAS) results depends on the genotyping algorithms used to establish the association. This paper initiated the assessment of the impact of the Corrected Robust Linear Model with Maximum Likelihood Classification (CRLMM) genotyping quality on identifying real significant genes in a GWAS with large sample sizes. With microarray image data from the Wellcome Trust Case-Control Consortium (WTCCC), 1991 individuals with coronary artery disease (CAD) and 1500 controls, genetic associations were evaluated under various batch sizes and compositions. Experimental designs included different batch sizes of 250, 350, 500, 2000 samples with different distributions of cases and controls in each batch with either randomized or simply combined (4:3 case-control ratios) or separate case-control samples as well as whole 3491 samples. The separate composition could create 2-3% discordance in the single nucleotide polymorphism (SNP) results for quality control/statistical analysis and might contribute to the lack of reproducibility between GWAS. CRLMM shows high genotyping accuracy and stability to batch effects. According to the genotypic and allelic tests (P

2019-09-26

2019-09-26