Economic burden of COVID-19 for employers and employees in the United States.

OBJECTIVE: Describe the economic burden of COVID-19 on employers and employees in the United States (US). METHODS: A targeted literature review was conducted to evaluate the impact of COVID-19 on US-based employers and employees in terms of healthcare resource utilization (HCRU), medical costs, and costs associated with work-loss. Searches were conducted in MEDLINE, Embase, and EconLit using a combination of disease terms, populations, and outcomes to identify articles published from January 2021 to November 4, 2022. As data from the employer perspective were lacking, additional literature related to influenza were included to contextualize the impact of COVID-19, as it shifts into an endemic state, within the existing respiratory illness landscape. RESULTS: A total of 41 articles were included in the literature review. Employer and employee perspectives were not well represented in the literature, and very few articles overlapped on any given outcome. HCRU, costs, and work impairment vary by community transmission levels, industry type, population demographics, telework ability, mitigation implementation measures, and company policies. Work-loss among COVID-19 cases were higher among the unvaccinated and in the week following diagnosis and for some, these continued for 6 months. HCRU is increased in those with COVID-19 and COVID-19-related HCRU can also continue for 6 months. CONCLUSIONS: COVID-19 continues to be a considerable burden to employers. The majority of COVID-19 cases impact working age adults. HCRU is mainly driven by outpatient visits, while direct costs are driven by hospitalization. Productivity loss is higher for unvaccinated individuals. An increased focus to support mitigation measures may minimize hospitalizations and work-loss. A data-driven approach to implementation of workplace policies, targeted communications, and access to timely and appropriate therapies for prevention and treatment may reduce health-related work-loss and associated cost burden.

In January 2020, the US government declared COVID-19 a public health emergency. This lasted until May 2023. To fight this health emergency, the US government provided free testing, vaccination, and treatment. Although the US government has declared the emergency over, COVID-19 continues to infect people. For people with private health insurance, costs associated with COVID-19 patient healthcare have now been transferred from the government to employers. In this study, we collected information from published scientific articles about the costs of COVID-19 for employers and workers in the US. We found that people who were not vaccinated against COVID-19 required more medical care and cost more than people who were vaccinated. In some cases, this trend lasted for as long as 6 months. This was mostly because of workers missing work, not working effectively while sick, and needing to be hospitalized. People who could work from home, whose companies had policies to prevent infections, and who took steps to avoid getting infected needed less medical care and missed work less often. This information may be used to help develop policies, communications, and guidance to prevent COVID-19 and limit its impact on employers and workers.

Maternal Tdap and influenza vaccination uptake 2017-2021 in the United States: Implications for maternal RSV vaccine uptake in the future.

BACKGROUND: Assessment of maternal vaccine coverage is important for understanding and quantifying the impact of currently recommended vaccines as well as modeling the potential impact of future vaccines. However, existing data lack detail regarding uptake according to week of gestational age (wGA). Such granularity is valuable for more accurate estimation of vaccine impact. OBJECTIVE: To summarize contemporary maternal Tdap vaccination uptake, overall, yearly, and by wGA, and maternal influenza vaccination uptake, overall, by influenza observation year, immunization month, and delivery month, in the US. METHODS: Female patients 18-49 years of age with a pregnancy resulting in a live born infant (i.e., delivery) between 2017 and 2021 were selected from the Optum electronic health records (EHRs) database. Recently published gestational age algorithms were utilized to estimate wGA. RESULTS: Of 1,021,260 deliveries among 886,660 women between 2017-2021, 55.1% had Tdap vaccination during pregnancy; vaccine coverage varied slightly by year (2017: 56.6%; 2018: 55.2%; 2019: 55.2%; 2020: 54.7%; 2021: 52.1%). Most (64.4%) maternal Tdap vaccinations occurred 27-32 wGA; 79.5% occurred during the entire 10-week recommended vaccination window (27-36 wGA). In the evaluation of influenza vaccination uptake (n=798,113 deliveries; 714,841 women), 33.5% of deliveries had influenza vaccination during influenza observation years 2017-2021, most (73.0%) of which occurred during influenza peak activity months (October-January) with approximately one-quarter (27.0%) of vaccinations having occurred during the off-peak months, mostly in September. CONCLUSIONS: In this large contemporary analysis of EHR data, uptake of Tdap vaccination during pregnancy was consistent with previously published estimates; notably, most vaccination occurred early in the recommended 27-36 wGA window. Maternal influenza vaccination uptake largely correlated with peak influenza activity months and not gestational age. These study findings may have important implications for estimating the potential uptake and impact of future maternal vaccines.

COVID-19 vaccine effectiveness among immunocompromised populations: a targeted literature review of real-world studies.

INTRODUCTION: From July through October of 2021, several countries issued recommendations for increased COVID-19 vaccine protection for individuals with one or more immunocompromised (IC) conditions. It is critically important to understand the vaccine effectiveness (VE) of COVID-19 vaccines among IC populations as recommendations are updated over time in response to the evolving COVID-19 pandemic. AREAS COVERED: A targeted literature review was conducted to identify real-world studies that assessed COVID-19 VE in IC populations between December 2020 and September 2021. A total of 10 studies from four countries were identified and summarized in this review. EXPERT OPINION: VE of the widely available COVID-19 vaccines, including BNT162b2 (Pfizer/BioNTech), mRNA-1273 (Moderna), Ad26.COV2.S (Janssen), and ChAdOx1 nCoV-19 (Oxford/AstraZeneca), ranged from 64% to 90% against SARS-CoV-2 infection, 73% to 84% against symptomatic illness, 70% to 100% against severe illness, and 63% to 100% against COVID-19-related hospitalization among the fully vaccinated IC populations included in the studies. COVID-19 VE for most outcomes in the IC populations included in these studies were lower than in the general populations. These findings provide preliminary evidence that the IC population requires greater protective measures to prevent COVID-19 infection and associated illness, hence should be prioritized while implementing recommendations of additional COVID-19 vaccine doses.

Network Analysis and Transcriptome Profiling Identify Autophagic and Mitochondrial Dysfunctions in SARS-CoV-2 Infection.

Analyzing host cells' transcriptional response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection will help delineate biological processes underlying viral pathogenesis. First, analysis of expression profiles of lung cell lines A549 and Calu3 revealed upregulation of antiviral interferon signaling genes in response to all three SARS-CoV-2, MERS-CoV, or influenza A virus (IAV) infections. However, perturbations in expression of genes involved in inflammatory, mitochondrial, and autophagy processes were specifically observed in SARS-CoV-2-infected cells. Next, a validation study in infected human nasopharyngeal samples also revealed perturbations in autophagy and mitochondrial processes. Specifically, mTOR expression, mitochondrial ribosomal, mitochondrial complex I, lysosome acidification, and mitochondrial fission promoting genes were concurrently downregulated in both infected cell lines and human samples. SARS-CoV-2 infection impeded autophagic flux either by upregulating GSK3B in lung cell lines or by downregulating autophagy genes, SNAP29, and lysosome acidification genes in human samples, contributing to increased viral replication. Therefore, drugs targeting lysosome acidification or autophagic flux could be tested as intervention strategies. Finally, age-stratified SARS-CoV-2-positive human data revealed impaired upregulation of chemokines, interferon-stimulated genes, and tripartite motif genes that are critical for antiviral signaling. Together, this analysis has revealed specific aspects of autophagic and mitochondrial function that are uniquely perturbed in SARS-CoV-2-infected host cells.

A retrospective study of in-hospital mortality in patients with idiopathic pulmonary fibrosis between 2015 and 2018.

Hospitalizations are common in patients with idiopathic pulmonary fibrosis (IPF) and are associated with high mortality. We used data from the Premier Healthcare Database to determine in-hospital mortality rates and the factors associated with in-hospital mortality in patients with IPF in the era of approved antifibrotic drugs.The Premier Healthcare Database is a detailed and broadly representative database of hospital admissions and discharges in the US. Patients with IPF who were hospitalized between 1 January 2015 and 28 February 2018 were identified using a diagnostic algorithm comprising International Classification of Diseases -9 and International Classification of Diseases -10 diagnostic codes and billing data. Associations between patient-, hospital- and treatment-related factors and a composite outcome of death during the index visit, lung transplant during the index visit but >1 day after admission, or death during a readmission within 90 days of the index visit were analyzed using logistic regression.The cohort comprised 9667 hospitalized patients with IPF. In total, 1414 patients (14.6%) met the composite outcome: 1036 (10.7%) died during the index visit, 371 (3.8%) died during a readmission within 90 days; 7 (0.1%) underwent lung transplant >1 day after admission. Factors significantly associated with a higher risk of the composite outcome included mechanical ventilation (odds ratio 6.41 [95% CI: 5.24, 7.84]), admission to the intensive care unit (1.73 [1.49, 2.00]), attendance by a critical care physician (2.12 [1.33, 3.38]), older age (1.20 [1.12, 1.28] per 10-year increase), and use of intravenous steroids (1.16 [1.00, 1.34]), intravenous antibiotics (1.49 [1.22, 1.83]) and opioids (3.41 [2.95, 3.93]). Factors significantly associated with a lower risk of the composite outcome included female sex (0.70 [0.61, 0.80]), comorbid chronic obstructive pulmonary disease (0.69 [0.60, 0.78]), attendance by a family medicine physician (0.67 [0.48, 0.94]) or internal medicine physician (0.59 [0.46, 0.75]), and use of oral steroids (0.62 [0.51, 0.77]), statins (0.76 [0.67, 0.87]) and proton pump inhibitors (0.80 [0.70, 0.92]).In conclusion, patients with IPF are at risk of mortality during a hospital stay or readmission within 90 days, particularly those who receive mechanical ventilation.

lncRNAKB, a knowledgebase of tissue-specific functional annotation and trait association of long noncoding RNA.

Long non-coding RNA Knowledgebase (lncRNAKB) is an integrated resource for exploring lncRNA biology in the context of tissue-specificity and disease association. A systematic integration of annotations from six independent databases resulted in 77,199 human lncRNA (224,286 transcripts). The user-friendly knowledgebase covers a comprehensive breadth and depth of lncRNA annotation. lncRNAKB is a compendium of expression patterns, derived from analysis of RNA-seq data in thousands of samples across 31 solid human normal tissues (GTEx). Thousands of co-expression modules identified via network analysis and pathway enrichment to delineate lncRNA function are also accessible. Millions of expression quantitative trait loci (cis-eQTL) computed using whole genome sequence genotype data (GTEx) can be downloaded at lncRNAKB that also includes tissue-specificity, phylogenetic conservation and coding potential scores. Tissue-specific lncRNA-trait associations encompassing 323 GWAS (UK Biobank) are also provided. LncRNAKB is accessible at http://www.lncrnakb.org/ , and the data are freely available through Open Science Framework ( https://doi.org/10.17605/OSF.IO/RU4D2 ).

Network Analysis and Transcriptome Profiling Identify Autophagic and Mitochondrial Dysfunctions in SARS-CoV-2 Infection.

Analyzing host transcriptional changes in response to SARS-CoV-2 infection will help delineate biological processes underlying viral pathogenesis. Comparison of expression profiles of lung cell lines A549 (infected with either SARS-CoV-2 (with ACE2 expression)) or Influenza A virus (IAV)) and Calu3 (infected with SARS-CoV-2 or MERS-CoV) revealed upregulation of the antiviral interferon signaling in all three viral infections. However, perturbations in inflammatory, mitochondrial, and autophagy processes were specifically observed in SARS-CoV-2 infected cells. Validation of findings from cell line data revealed perturbations in autophagy and mitochondrial processes in the infected human nasopharyngeal samples. Specifically, downregulation of mTOR expression, mitochondrial ribosomal, mitochondrial complex I, and lysosome acidification genes were concurrently observed in both infected cell lines and human datasets. Furthermore, SARS-CoV-2 infection impedes autophagic flux by upregulating GSK3B in lung cell lines, or by downregulating autophagy genes, SNAP29 and lysosome acidification genes in human samples, contributing to increased viral replication. Therefore, drugs targeting lysosome acidification or autophagic flux could be tested as intervention strategies. Additionally, downregulation of MTFP1 (in cell lines) or SOCS6 (in human samples) results in hyperfused mitochondria and impede proper interferon response. Coexpression networks analysis identifies correlated clusters of genes annotated to inflammation and mitochondrial processes that are misregulated in SARS-CoV-2 infected cells. Finally, comparison of age stratified human gene expression data revealed impaired upregulation of chemokines, interferon stimulated and tripartite motif genes that are critical for antiviral signaling. Together, this analysis has revealed specific aspects of autophagic and mitochondrial function that are uniquely perturbed in SARS-CoV-2 infection.

Inpatient Healthcare Resource Utilization, Costs, and Mortality in Adult Patients with Acute Graft-versus-Host Disease, Including Steroid-Refractory or High-Risk Disease, following Allogeneic Hematopoietic Cell Transplantation.

Acute graft-versus-host disease (GVHD) contributes to poor outcomes following allogeneic hematopoietic cell transplantation (HCT). Data are limited regarding the economic burden of acute GVHD, particularly steroid-refractory or high-risk (SR/HR) disease. This retrospective analysis of the Premier Healthcare Database reports inpatient healthcare resource utilization (HCRU), costs, and mortality during initial hospitalization for allogeneic HCT and through 100 days post-HCT among patients who developed acute GVHD, including a subgroup with SR/HR disease, compared with patients without GVHD. The analysis included adults discharged for first HCT between January 1, 2011, and June 30, 2016 (acute GVHD, n = 906; SR/HR acute GVHD, n = 158; no GVHD, n = 1529). During the initial hospitalization for HCT, patients with acute GVHD and SR/HR acute GVHD (n = 455 and 125, respectively) had significantly longer median lengths of stay (31 and 46 days versus 24 days) and higher median total costs ($153,849 and $205,880 versus $97,417) versus patients with no GVHD (n = 1529; P < .0001 for all). During the 100-day post-HCT period, patients with acute GVHD and SR/HR acute GVHD had higher readmission rates (78.3% and 77.2% versus 28.3%; P < .0001) and inpatient mortality rates (20.2% and 35.4% versus 8.9%; P < .0001) versus patients with no GVHD. In summary, acute GVHD, especially SR/HR disease, is associated with longer inpatient stays, higher readmission rates, and higher inpatient mortality compared with no GVHD.

In-Hospital Mortality in Patients with Idiopathic Pulmonary Fibrosis: A US Cohort Study.

PURPOSE: In patients with idiopathic pulmonary fibrosis (IPF), hospitalizations are associated with high mortality. We sought to determine in-hospital mortality rates and factors associated with in-hospital mortality in patients with IPF. METHODS: Patients with IPF were identified from the Premier Healthcare Database, a representative administrative dataset that includes > 20% of hospital discharges in the US, using an algorithm based on diagnostic codes and billing data. We used logistic regression to analyze associations between patient-, hospital-, and treatment-related characteristics and a composite primary outcome of death during the index visit, lung transplant during the index visit and > 1 day after admission, or death during a readmission within 90 days. RESULTS: The cohort comprised 6665 patients with IPF hospitalized between October 2011 and October 2014. A total of 963 (14.4%) met the primary outcome. Factors significantly associated with a higher risk of the primary outcome included mechanical ventilation [odds ratio 4.65 (95% CI 3.73, 5.80)], admission to the intensive care unit [1.83 (1.52, 2.21)], treatment with opioids (3.06 [2.57, 3.65]), and a diagnosis of pneumonia [1.44 (1.21, 1.71)]. Factors significantly associated with a lower risk included concurrent chronic obstructive pulmonary disease [0.65 (0.55, 0.77)] and female sex [0.67 (0.57, 0.79)]. CONCLUSIONS: Patients with IPF, particularly those receiving mechanical ventilation or intensive care, are at substantial risk of death or lung transplant during hospitalization or death during a readmission within 90 days.

Replication of Epigenetic Postpartum Depression Biomarkers and Variation with Hormone Levels.

DNA methylation variation at HP1BP3 and TTC9B is modified by estrogen exposure in the rodent hippocampus and was previously shown to be prospectively predictive of postpartum depression (PPD) when modeled in antenatal blood. The objective of this study was to replicate the predictive efficacy of the previously established model in women with and without a previous psychiatric diagnosis and to understand the effects of changing hormone levels on PPD biomarker loci. Using a statistical model trained on DNA methylation data from N=51 high-risk women, we prospectively predicted PPD status in an independent N=51 women using first trimester antenatal gene expression levels of HP1BP3 and TTC9B, with an area under the receiver operator characteristic curve (AUC) of 0.81 (95% CI: 0.69-0.92, p<5 × 10(-4)). Modeling DNA methylation of these genes in N=240 women without a previous psychiatric diagnosis resulted in a cross-sectional prediction of PPD status with an AUC of 0.81 (95% CI: 0.68-0.93, p=0.01). TTC9B and HP1BP3 DNA methylation at early antenatal time points showed moderate evidence for association to the change in estradiol and allopregnanolone over the course of pregnancy, suggesting that epigenetic variation at these loci may be important for mediating hormonal sensitivity. In addition both loci showed PPD-specific trajectories with age, possibly mediated by age-associated hormonal changes. The data add to the growing body of evidence suggesting that PPD is mediated by differential gene expression and epigenetic sensitivity to pregnancy hormones and that modeling proxies of this sensitivity enable accurate prediction of PPD.

Systematic review of genome-wide gene expression studies of bipolar disorder.

BACKGROUND: Numerous genome-wide gene expression studies of bipolar disorder (BP) have been carried out. These studies are heterogeneous, underpowered and use overlapping samples. We conducted a systematic review of these studies to synthesize the current findings. METHODS: We identified all genome-wide gene expression studies on BP in humans. We then carried out a quantitative mega-analysis of studies done with post-mortem brain tissue. We obtained raw data from each study and used standardized procedures to process and analyze the data. We then combined the data and conducted three separate mega-analyses on samples from 1) any region of the brain (9 studies); 2) the prefrontal cortex (PFC) (6 studies); and 3) the hippocampus (2 studies). To minimize heterogeneity across studies, we focused primarily on the most numerous, recent and comprehensive studies. RESULTS: A total of 30 genome-wide gene expression studies of BP done with blood or brain tissue were identified. We included 10 studies with data on 211 microarrays on 57 unique BP cases and 229 microarrays on 60 unique controls in the quantitative mega-analysis. A total of 382 genes were identified as significantly differentially expressed by the three analyses. Eleven genes survived correction for multiple testing with a q-value < 0.05 in the PFC. Among these were FKBP5 and WFS1, which have been previously implicated in mood disorders. Pathway analyses suggested a role for metallothionein proteins, MAP Kinase phosphotases, and neuropeptides. CONCLUSION: We provided an up-to-date summary of results from gene expression studies of the brain in BP. Our analyses focused on the highest quality data available and provided results by brain region so that similarities and differences can be examined relative to disease status. The results are available for closer inspection on-line at Metamoodics [http://metamoodics.igm.jhmi.edu/], where investigators can look up any genes of interest and view the current results in their genomic context and in relation to leading findings from other genomic experiments in bipolar disorder.

Converging Evidence for Epistasis between ANK3 and Potassium Channel Gene KCNQ2 in Bipolar Disorder.

Genome-wide association studies (GWAS) have implicated ANK3 as a susceptibility gene for bipolar disorder (BP). We examined whether epistasis with ANK3 may contribute to the "missing heritability" in BP. We first identified via the STRING database 14 genes encoding proteins with prior biological evidence that they interact molecularly with ANK3. We then tested for statistical evidence of interactions between SNPs in these genes in association with BP in a discovery GWAS dataset and two replication GWAS datasets. The most significant interaction in the discovery GWAS was between SNPs in ANK3 and KCNQ2 (p = 3.18 × 10(-8)). A total of 31 pair-wise interactions involving combinations between two SNPs from KCNQ2 and 16 different SNPs in ANK3 were significant after permutation. Of these, 28 pair-wise interactions were significant in the first replication GWAS. None were significant in the second replication GWAS, but the two SNPs from KCNQ2 were found to significantly interact with five other SNPs in ANK3, suggesting possible allelic heterogeneity. KCNQ2 forms homo- and hetero-meric complexes with KCNQ3 that constitute voltage-gated potassium channels in neurons. ANK3 is an adaptor protein that, through its interaction with KCNQ2 and KCNQ3, directs the localization of this channel in the axon initial segment (AIS). At the AIS, the KCNQ2/3 complex gives rise to the M-current, which stabilizes the neuronal resting potential and inhibits repetitive firing of action potentials. Thus, these channels act as "dampening" components and prevent neuronal hyperactivity. The interactions between ANK3 and KCNQ2 merit further investigation, and if confirmed, may motivate a new line of research into a novel therapeutic target for BP.

A review of potassium channels in bipolar disorder.

Although bipolar disorder (BP) is one of the most heritable psychiatric conditions, susceptibility genes for the disorder have yet to be conclusively identified. It is likely that variants in multiple genes across multiple pathways contribute to the genotype-phenotype relationship in the affected population. Recent evidence from genome-wide association studies implicates an entire class of genes related to the structure and regulation of ion channels, suggesting that the etiology of BP may arise from channelopathies. In this review, we examine the evidence for this hypothesis, with a focus on the potential role of voltage-gated potassium channels. We consider evidence from genetic and expression studies, and discuss the potential underlying biology. We consider animal models and treatment implications of the involvement of potassium ion channelopathy in BP. Finally, we explore intriguing parallels between BP and epilepsy, the signature channelopathy of the central nervous system.

Meta-analysis of genetic association studies on bipolar disorder.

Numerous candidate gene association studies of bipolar disorder (BP) have been carried out, but the results have been inconsistent. Individual studies are typically underpowered to detect associations with genes of small effect sizes. We conducted a meta-analysis of published candidate gene studies to evaluate the cumulative evidence. We systematically searched for all published candidate gene association studies of BP. We then carried out a random-effects meta-analysis on all polymorphisms that were reported on by three or more case-control studies. The results from meta-analyses of these genes were compared with the findings from a recent mega-analysis of eleven genome-wide association studies (GWAS) in BP performed by the Psychiatric GWAS Consortium (PGC). A total of 487 articles were included in our review. Among these, 33 polymorphisms in 18 genes were reported on by three or more case-control studies and included in the random-effects meta-analysis. Polymorphisms in BDNF, DRD4, DAOA, and TPH1, were found to be nominally significant with a P-value < 0.05. However, none of the findings were significant after correction for multiple testing. Moreover, none of these polymorphisms were nominally significant in the PGC-BP GWAS. A number of plausible candidate genes have been previously associated with BP. However, the lack of robust findings in our review of these candidate genes highlights the need for more atheoretical approaches to study the genetics of BP afforded by GWAS. The results of this meta-analysis and from other on-going genomic experiments in BP are available online at Metamoodics (http://metamoodics.igm.jhmi.edu).

Association study of serotonin pathway genes in attempted suicide.

Epidemiological studies, such as family, twin, and adoption studies, demonstrate the presence of a heritable component to both attempted and completed suicide. Some of this heritability is accounted for by the presence of comorbid psychiatric disorders, but the evidence also indicates that a portion of this heritability is specific to suicidality. The serotonergic system has been studied extensively in this phenotype, but findings have been inconsistent, possibly due to the presence of multiple susceptibility variants and/or gene-gene interactions. In this study, we genotyped 174 tag and coding single nucleotide polymorphisms (SNPs) from 17 genes within the serotonin pathway on 516 subjects with a major mood disorder and a history of a suicide attempt (cases) and 515 healthy controls, with the goal of capturing the common genetic variation across each of these candidate genes. We tested the 174 markers in single-SNP, haplotype, gene-based, and epistasis analyses. While these association analyses identified multiple marginally significant SNPs, haplotypes, genes, and interactions, none of them survived correction for multiple testing. Additional studies, including assessment in larger sample sets and deep resequencing to identify rare causal variants, may be required to fully understand the role that the serotonin pathway plays in suicidal behavior.

Data mining approaches for genome-wide association of mood disorders.

BACKGROUND: Mood disorders are highly heritable forms of major mental illness. A major breakthrough in elucidating the genetic architecture of mood disorders was anticipated with the advent of genome-wide association studies (GWAS). However, to date few susceptibility loci have been conclusively identified. The genetic etiology of mood disorders appears to be quite complex, and as a result, alternative approaches for analyzing GWAS data are needed. Recently, a polygenic scoring approach that captures the effects of alleles across multiple loci was successfully applied to the analysis of GWAS data in schizophrenia and bipolar disorder (BP). However, this method may be overly simplistic in its approach to the complexity of genetic effects. Data mining methods are available that may be applied to analyze the high dimensional data generated by GWAS of complex psychiatric disorders. RESULTS: We sought to compare the performance of five data mining methods, namely, Bayesian networks, support vector machine, random forest, radial basis function network, and logistic regression, against the polygenic scoring approach in the analysis of GWAS data on BP. The different classification methods were trained on GWAS datasets from the Bipolar Genome Study (2191 cases with BP and 1434 controls) and their ability to accurately classify case/control status was tested on a GWAS dataset from the Wellcome Trust Case Control Consortium. CONCLUSION: The performance of the classifiers in the test dataset was evaluated by comparing area under the receiver operating characteristic curves. Bayesian networks performed the best of all the data mining classifiers, but none of these did significantly better than the polygenic score approach. We further examined a subset of single-nucleotide polymorphisms (SNPs) in genes that are expressed in the brain, under the hypothesis that these might be most relevant to BP susceptibility, but all the classifiers performed worse with this reduced set of SNPs. The discriminative accuracy of all of these methods is unlikely to be of diagnostic or clinical utility at the present time. Further research is needed to develop strategies for selecting sets of SNPs likely to be relevant to disease susceptibility and to determine if other data mining classifiers that utilize other algorithms for inferring relationships among the sets of SNPs may perform better.

The promise and reality of pharmacogenetics in psychiatry.

Existing psychotropic medications for the treatment of mental illnesses, including antidepressants, mood stabilizers, and antipsychotics, are clinically suboptimal. They are effective in only a subset of patients or produce partial responses, and they are often associated with debilitating side effects that discourage adherence. There is growing enthusiasm in the promise of pharmacogenetics to personalize the use of these treatments to maximize their efficacy and tolerability; however, there is still a long way to go before this promise becomes a reality. This article reviews the progress that has been made in research toward understanding how genetic factors influence psychotropic drug responses and the challenges that lie ahead in translating the research findings into clinical practices that yield tangible benefits for patients with mental illnesses.

Case-control association study of TGOLN2 in attempted suicide.

Family, twin, and adoption studies provide convincing evidence for a genetic contribution to suicidal behavior. The heritability for suicidal behavior depends in part on the transmission of psychiatric disorders, such as mood disorders and substance use disorders, but is also partly independent of them. Three linkage studies using the attempted suicide phenotype in pedigrees with bipolar disorder, major depression, or alcoholism have provided consistent evidence that 2p11-12 harbors a susceptibility gene for attempted suicide. A microarray expression study using postmortem brain samples has implicated a gene from the 2p11-12 candidate region, the trans-Golgi network protein 2 (TGOLN2) gene, as being consistently up-regulated in suicide cases as compared to controls. Here, we present a TGOLN2 case-control association study using nine single nucleotide polymorphisms (SNPs). These nine SNPs, which include seven tag SNPs and two coding SNPs, have been genotyped in 517 mood disorder subjects with a history of attempted suicide and 515 normal controls. Allelic and genotypic analyses of the case-control sample did not provide evidence for association with the attempted suicide phenotype. Eight of the nine SNPs provided supportive evidence for association (P-values ranging from 0.008 to 0.03) when we compared the attempted suicide cases with a history of alcoholism to the attempted suicide cases without a history of alcoholism. However, this association finding was not replicated in an independent sample. Taken together, these analyses do not provide support for the hypothesis that common genetic variation in TGOLN2 contributes significantly to the risk for attempted suicide in subjects with major mood disorders.

The promise and reality of pharmacogenetics in psychiatry.

Existing psychotropic medications for the treatment of mental illnesses, including antidepressants, mood stabilizers, and antipsychotics, are clinically suboptimal. They are effective in only a subset of patients or produce partial responses, and they are often associated with debilitating side effects that discourage adherence. There is growing enthusiasm in the promise of pharmacogenetics to personalize the use of these treatments to maximize their efficacy and tolerability; however, there is still a long way to go before this promise becomes a reality. This article reviews the progress that has been made in research toward understanding how genetic factors influence psychotropic drug responses and the challenges that lie ahead in translating the research findings into clinical practices that yield tangible benefits for patients with mental illnesses.

TileProbe: modeling tiling array probe effects using publicly available data.

MOTIVATION: Individual probes on an Affymetrix tiling array usually behave differently. Modeling and removing these probe effects are critical for detecting signals from the array data. Current data processing techniques either require control samples or use probe sequences to model probe-specific variability, such as with MAT. Although the MAT approach can be applied without control samples, residual probe effects continue to distort the true biological signals. RESULTS: We propose TileProbe, a new technique that builds upon the MAT algorithm by incorporating publicly available data sets to remove tiling array probe effects. By using a large number of these readily available arrays, TileProbe robustly models the residual probe effects that MAT model cannot explain. When applied to analyzing ChIP-chip data, TileProbe performs consistently better than MAT across a variety of analytical conditions. This shows that TileProbe resolves the issue of probe-specific effects more completely. AVAILABILITY: http://www.biostat.jhsph.edu/ approximately hji/cisgenome/index_files/tileprobe.htm.