South Asian medical cohorts reveal strong founder effects and high rates of homozygosity.

The benefits of large-scale genetic studies for healthcare of the populations studied are well documented, but these genetic studies have traditionally ignored people from some parts of the world, such as South Asia. Here we describe whole genome sequence (WGS) data from 4806 individuals recruited from the healthcare delivery systems of Pakistan, India and Bangladesh, combined with WGS from 927 individuals from isolated South Asian populations. We characterize population structure in South Asia and describe a genotyping array (SARGAM) and imputation reference panel that are optimized for South Asian genomes. We find evidence for high rates of reproductive isolation, endogamy and consanguinity that vary across the subcontinent and that lead to levels of rare homozygotes that reach 100 times that seen in outbred populations. Founder effects increase the power to associate functional variants with disease processes and make South Asia a uniquely powerful place for population-scale genetic studies.

The psychosocial health, experiences and needs of older adults and care partners during the first surge of the COVID-19 pandemic: a mixed-methods study.

BACKGROUND: Minimal research has leveraged qualitative data methods to gain a better understanding of the experiences and needs of older adults (OAs) and care partners of OAs with and without Alzheimer's Disease (AD) and AD-related dementias (AD/ADRD) during the first surge of the COVID-19 pandemic. In this study, we: 1) quantitatively evaluated the psychosocial health of community-dwelling OAs; 2) quantitatively evaluated the perceived stress of care partners for OAs; 3) qualitatively characterized the experiences and needs of community-dwelling OAs and their care partners; and 4) explored differences in the experiences of care partners of OAs with and without AD/ADRD during the first surge of the COVID-19 pandemic in the New York metropolitan area. METHODS: In this mixed-methods study, telephone interviews were conducted with 26 OAs and 29 care partners (16 of whom cared for OAs with AD/ADRD) from April to July 2020. Quantitative data included: demographics; clinical characteristics (Katz Index of independence in activities of daily living (Katz ADL) and the Lawton-Brody instrumental activities of daily living scale (Lawton-Brody)); and psychosocial health: stress was assessed via the Perceived Stress Scale (PSS), social isolation via the Lubben Social Network Scale (LSNS), loneliness via the DeJong Loneliness Scale (DeJong), and depression and anxiety via the Patient Health Questionnaire-Anxiety and Depression (PHQ). Qualitative questions focused on uncovering the experiences and needs of OAs and their care partners. RESULTS: OAs (N = 26) were mostly female (57.7%), and White (76.9%), average age of 81.42 years. While OAs were independent (M = 5.60, Katz ADL) and highly functional (M = 6.92, Lawton-Brody), and expressed low levels of loneliness, stress, depression and anxiety (M = 1.95 on DeJong; M = 12.67 on PSS; M = 1.05 on PHQ depression; and M = 1.09 on PHQ anxiety), open-ended questions elicited themes of fear and worry. Care partners (N = 29) were mostly female (75.9%), White (72.4%), and married (72.4%), and reported moderate stress (M = 16.52 on the PSS), as well as a psychological impact of the pandemic. CONCLUSIONS: Early in the pandemic, OAs reported minimal stress and loneliness; this may have been related to their reports of frequent interaction with family, even if only virtually. By contrast, care partners were moderately stressed and worried, potentially more than usual due to the additional challenges they face when trying to meet their loved ones' needs during a pandemic.

A whole genome sequencing study of moderate to severe asthma identifies a lung function locus associated with asthma risk.

Genome-wide association studies (GWAS) have identified many common variant loci associated with asthma susceptibility, but few studies investigate the genetics underlying moderate-to-severe asthma risk. Here, we present a whole-genome sequencing study comparing 3181 moderate-to-severe asthma patients to 3590 non-asthma controls. We demonstrate that asthma risk is genetically correlated with lung function measures and that this component of asthma risk is orthogonal to the eosinophil genetics that also contribute to disease susceptibility. We find that polygenic scores for reduced lung function are associated with younger asthma age of onset. Genome-wide, seven previously reported common asthma variant loci and one previously reported lung function locus, near THSD4, reach significance. We replicate association of the lung function locus in a recently published GWAS of moderate-to-severe asthma patients. We additionally replicate the association of a previously reported rare (minor allele frequency < 1%) coding variant in IL33 and show significant enrichment of rare variant burden in genes from common variant allergic disease loci. Our findings highlight the contribution of lung function genetics to moderate-to-severe asthma risk, and provide initial rare variant support for associations with moderate-to-severe asthma risk at several candidate genes from common variant loci.

The Virulence of Grief in the Pandemic: Bereavement Overload During COVID.

The COVID-19 pandemic brought about bereavement overload as a risk factor for complicated grief. Bereavement overload (BO) describes individuals' reactions to losses transpiring in a quick succession, without the time and opportunity for coping [9]. It can occur during catastrophic events and impact everyone experiencing the loss.With the high death toll from COVID-19, many people have lost multiple loved ones followed by an abbreviated grieving process due to the nature of the pandemic. This can have psychosocial impact on survivors for years. One of the evolving roles of Palliative Care within and after the pandemic should be to recognize those suffering from BO. Obtaining loss histories may identify those at risk of pathologic grief to provide preventive bereavement care.We present three cases encountered in our health system during the COVID-19 pandemic amongst a family member, a patient, and a healthcare provider. In each case the Palliative Care Team worked closely with these individuals to identify COVID-associated BO and helped them reconcile their unresolved grief to be able to move forward. These cases reflect only a fraction of those who experienced loss during the pandemic, but they illustrate how grief can be complicated by the pandemic for everyone involved.Palliative Care will have a crucial role moving forward, in treating the pandemic of complicated grief within the pandemic to adapt to the needs of all survivors, as we realize the effects of COVID will last long after its virulence has waned.

Prognostic and Predictive Biomarkers in Patients With Coronavirus Disease 2019 Treated With Tocilizumab in a Randomized Controlled Trial.

OBJECTIVES: To explore candidate prognostic and predictive biomarkers identified in retrospective observational studies (interleukin-6, C-reactive protein, lactate dehydrogenase, ferritin, lymphocytes, monocytes, neutrophils, d-dimer, and platelets) in patients with coronavirus disease 2019 pneumonia after treatment with tocilizumab, an anti-interleukin-6 receptor antibody, using data from the COVACTA trial in patients hospitalized with severe coronavirus disease 2019 pneumonia. DESIGN: Exploratory analysis from a multicenter, randomized, double-blind, placebo-controlled, phase 3 trial. SETTING: Hospitals in North America and Europe. PATIENTS: Adults hospitalized with severe coronavirus disease 2019 pneumonia receiving standard care. INTERVENTION: Randomly assigned 2:1 to IV tocilizumab 8 mg/kg or placebo. MEASUREMENTS AND MAIN RESULTS: Candidate biomarkers were measured in 295 patients in the tocilizumab arm and 142 patients in the placebo arm. Efficacy outcomes assessed were clinical status on a seven-category ordinal scale (1, discharge; 7, death), mortality, time to hospital discharge, and mechanical ventilation (if not receiving it at randomization) through day 28. Prognostic and predictive biomarkers were evaluated continuously with proportional odds, binomial or Fine-Gray models, and additional sensitivity analyses. Modeling in the placebo arm showed all candidate biomarkers except lactate dehydrogenase and d-dimer were strongly prognostic for day 28 clinical outcomes of mortality, mechanical ventilation, clinical status, and time to hospital discharge. Modeling in the tocilizumab arm showed a predictive value of ferritin for day 28 clinical outcomes of mortality (predictive interaction, p = 0.03), mechanical ventilation (predictive interaction, p = 0.01), and clinical status (predictive interaction, p = 0.02) compared with placebo. CONCLUSIONS: Multiple biomarkers prognostic for clinical outcomes were confirmed in COVACTA. Ferritin was identified as a predictive biomarker for the effects of tocilizumab in the COVACTA patient population; high ferritin levels were associated with better clinical outcomes for tocilizumab compared with placebo at day 28.

Inhaled JAK inhibitor GDC-0214 reduces exhaled nitric oxide in patients with mild asthma: A randomized, controlled, proof-of-activity trial.

BACKGROUND: The Janus kinase (JAK) pathway mediates the activity of many asthma-relevant cytokines, including IL-4 and IL-13. GDC-0214 is a potent, inhaled, small-molecule JAK inhibitor being developed for the treatment of asthma. OBJECTIVE: We sought to determine whether GDC-0214 reduces fractional exhaled nitric oxide (Feno), a JAK1-dependent biomarker of airway inflammation, in patients with mild asthma. METHODS: We conducted a double-blind, randomized, placebo-controlled, phase 1 proof-of-activity study in adults with mild asthma and Feno higher than 40 parts per billion (ppb). Subjects were randomized 2:1 (GDC-0214:placebo) into 4 sequential ascending-dose cohorts (1 mg once daily [QD], 4 mg QD, 15 mg QD, or 15 mg twice daily). All subjects received 4 days of blinded placebo, then 10 days of either active drug or placebo. The primary outcome was placebo-corrected percent reduction in Feno from baseline to day 14. Baseline was defined as the average Feno during the blinded placebo period. Pharmacokinetics, safety, and tolerability were also assessed. RESULTS: Thirty-six subjects (mean age, 28 years; 54% females) were enrolled. Mean Feno at baseline across all subjects was 93 ± 43 ppb. At day 14, placebo-corrected difference in Feno was -23% (95% CI, -37.3 to -9) for 15 mg QD and -42% (95% CI, -57 to -27.4) for 15 mg twice daily. Higher plasma exposure was associated with greater Feno reduction. No dose-limiting adverse events, serious adverse events, or treatment discontinuations occurred. There were no major imbalances in adverse events or laboratory findings, or evidence of systemic JAK inhibition. CONCLUSIONS: GDC-0214, an inhaled JAK inhibitor, caused dose-dependent reductions in Feno in mild asthma and was well tolerated without evidence of systemic toxicity.

LACC1 Regulates TNF and IL-17 in Mouse Models of Arthritis and Inflammation.

Both common and rare genetic variants of laccase domain-containing 1 (LACC1, previously C13orf31) are associated with inflammatory bowel disease, leprosy, Behcet disease, and systemic juvenile idiopathic arthritis. However, the functional relevance of these variants is unclear. In this study, we use LACC1-deficient mice to gain insight into the role of LACC1 in regulating inflammation. Following oral administration of Citrobacter rodentium, LACC1 knockout (KO) mice had more severe colon lesions compared with wildtype (WT) controls. Immunization with collagen II, a collagen-induced arthritis (CIA) model, resulted in an accelerated onset of arthritis and significantly worse arthritis and inflammation in LACC1 KO mice. Similar results were obtained in a mannan-induced arthritis model. Serum and local TNF in CIA paws and C. rodentium colons were significantly increased in LACC1 KO mice compared with WT controls. The percentage of IL-17A-producing CD4+ T cells was elevated in LACC1 KO mice undergoing CIA as well as aged mice compared with WT controls. Neutralization of IL-17, but not TNF, prevented enhanced mannan-induced arthritis in LACC1 KO mice. These data provide new mechanistic insight into the function of LACC1 in regulating TNF and IL-17 during inflammatory responses. We hypothesize that these effects contribute to immune-driven pathologies observed in individuals carrying LACC1 variants.

Previously reported placebo-response-associated variants do not predict patient outcomes in inflammatory disease Phase III trial placebo arms.

In clinical trials, a placebo response refers to improvement in disease symptoms arising from the psychological effect of receiving a treatment rather than the actual treatment under investigation. Previous research has reported genomic variation associated with the likelihood of observing a placebo response, but these studies have been limited in scope and have not been validated. Here, we analyzed whole-genome sequencing data from 784 patients undergoing placebo treatment in Phase III Asthma or Rheumatoid Arthritis trials to assess the impact of previously reported variation on patient outcomes in the placebo arms and to identify novel variants associated with the placebo response. Contrary to expectations based on previous reports, we did not observe any statistically significant associations between genomic variants and placebo treatment outcome. Our findings suggest that the biological origin of the placebo response is complex and likely to be variable between disease areas.

Enabling genome-wide association testing with multiple diseases and no healthy controls.

MOTIVATION: While large-scale whole genome sequencing is feasible the high costs compel investigators to focus on disease subjects. As a result large sequencing datasets of samples with different diseases are often readily available, but not healthy controls to contrast them with. While it is possible to perform an association study using only diseases, the associations could be driven by a disease acting as a control and not the focal disease. METHODS: We developed a genotype-on-phenotype reverse regression with a Bayesian spike and slab prior to enable association testing in datasets with multiple diseases. This method, referred to as revreg, flagged associations (both common and rare) that were driven by diseases that were not of primary interest. RESULTS: Based on simulations, revreg had 80% power to detect an odds ratio of 1.74 for common variants (3500 samples total) and 3.73 for rare variants (14,000 samples total), with minimal type I error. For common variants, we tested this method on 3657 whole genome sequenced samples aimed at discovering variants associated with disease risk of Chronic Obstructive Pulmonary Disease using three other diseases as controls. We demonstrated detection of six highly significant associations likely due to Age-Related Macular Degeneration. In an exome dataset of 8836 samples aimed at characterizing rare variants associated with disease risk of Asthma, using five other diseases as controls, we detected and removed genic regions due to AMD (C3, CFH, CFHR5, CFI, and DNMT3A) and RA (KRTAP13-4).

microbiomeDASim: Simulating longitudinal differential abundance for microbiome data.

An increasing emphasis on understanding the dynamics of microbial communities in various settings has led to the proliferation of longitudinal metagenomic sampling studies. Data from whole metagenomic shotgun sequencing and marker-gene survey studies have characteristics that drive novel statistical methodological development for estimating time intervals of differential abundance. In designing a study and the frequency of collection prior to a study, one may wish to model the ability to detect an effect, e.g., there may be issues with respect to cost, ease of access, etc. Additionally, while every study is unique, it is possible that in certain scenarios one statistical framework may be more appropriate than another. Here, we present a simulation paradigm implemented in the R Bioconductor software package microbiomeDASim available at http://bioconductor.org/packages/microbiomeDASim microbiomeDASim. microbiomeDASim allows investigators to simulate longitudinal differential abundant microbiome features with a variety of known functional forms with flexible parameters to control desired signal-to-noise ratio. We present metrics of success results on one particular method called metaSplines.

Analysis of protein-altering variants in telomerase genes and their association with MUC5B common variant status in patients with idiopathic pulmonary fibrosis: a candidate gene sequencing study.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) risk has a strong genetic component. Studies have implicated variations at several loci, including TERT, surfactant genes, and a single nucleotide polymorphism at chr11p15 (rs35705950) in the intergenic region between TOLLIP and MUC5B. Patients with IPF who have risk alleles at rs35705950 have longer survival from the time of IPF diagnosis than do patients homozygous for the non-risk allele, whereas patients with shorter telomeres have shorter survival times. We aimed to assess whether rare protein-altering variants in genes regulating telomere length are enriched in patients with IPF homozygous for the non-risk alleles at rs35705950. METHODS: Between Nov 1, 2014, and Nov 1, 2016, we assessed blood samples from patients aged 40 years or older and of European ancestry with sporadic IPF from three international phase 3 clinical trials (INSPIRE, CAPACITY, ASCEND), one phase 2 study (RIFF), and US-based observational studies (Vanderbilt Clinical Interstitial Lung Disease Registry and the UCSF Interstitial Lung Disease Clinic registry cohorts) at the Broad Institute (Cambridge, MA, USA) and Human Longevity (San Diego, CA, USA). We also assessed blood samples from non-IPF controls in several clinical trials. We did whole-genome sequencing to assess telomere length and identify rare protein-altering variants, stratified by rs35705950 genotype. We also assessed rare functional variation in TERT exons and compared telomere length and disease progression across genotypes. FINDINGS: We assessed samples from 1510 patients with IPF and 1874 non-IPF controls. 30 (3%) of 1046 patients with an rs35705950 risk allele had a rare protein-altering variant in TERT compared with 34 (7%) of 464 non-risk allele carriers (odds ratio 0·40 [95% CI 0·24-0·66], p=0·00039). Subsequent analyses identified enrichment of rare protein-altering variants in PARN and RTEL1, and rare variation in TERC in patients with IPF compared with controls. We expanded our study population to provide a more accurate estimation of rare variant frequency in these four loci, and to calculate telomere length. The proportion of patients with at least one rare variant in TERT, PARN, TERC, or RTEL1 was higher in patients with IPF than in controls (149 [9%] of 1739 patients vs 205 [2%] of 8645 controls, p=2·44 × 10-8). Patients with IPF who had a variant in any of the four identified telomerase component genes had telomeres that were 3·69-16·10% shorter than patients without a variant in any of the four genes and had an earlier mean age of disease onset than patients without one or more variants (65·1 years [SD 7·8] vs 67·1 years [7·9], p=0·004). In the placebo arms of clinical trials, shorter telomeres were significantly associated with faster disease progression (1·7% predicted forced vital capacity per kb per year, p=0·002). Pirfenidone had treatment benefit regardless of telomere length (p=4·24 × 10-8 for telomere length lower than the median, p=0·0044 for telomere length greater than the median). INTERPRETATION: Rare protein-altering variants in TERT, PARN, TERC, and RTEL1 are enriched in patients with IPF compared with controls, and, in the case of TERT, particularly in individuals without a risk allele at the rs35705950 locus. This suggests that multiple genetic factors contribute to sporadic IPF, which might implicate distinct mechanisms of pathogenesis and disease progression. FUNDING: Genentech, National Institutes of Health, Francis Family Foundation, Pulmonary Fibrosis Foundation, Nina Ireland Program for Lung Health, US Department of Veterans Affairs.

Comprehensive genomic analysis identifies pathogenic variants in maturity-onset diabetes of the young (MODY) patients in South India.

BACKGROUND: Maturity-onset diabetes of the young (MODY) is an early-onset, autosomal dominant form of non-insulin dependent diabetes. Genetic diagnosis of MODY can transform patient management. Earlier data on the genetic predisposition to MODY have come primarily from familial studies in populations of European origin. METHODS: In this study, we carried out a comprehensive genomic analysis of 289 individuals from India that included 152 clinically diagnosed MODY cases to identify variants in known MODY genes. Further, we have analyzed exome data to identify putative MODY relevant variants in genes previously not implicated in MODY. Functional validation of MODY relevant variants was also performed. RESULTS: We found MODY 3 (HNF1A; 7.2%) to be most frequently mutated followed by MODY 12 (ABCC8; 3.3%). They together account for ~ 11% of the cases. In addition to known MODY genes, we report the identification of variants in RFX6, WFS1, AKT2, NKX6-1 that may contribute to development of MODY. Functional assessment of the NKX6-1 variants showed that they are functionally impaired. CONCLUSIONS: Our findings showed HNF1A and ABCC8 to be the most frequently mutated MODY genes in south India. Further we provide evidence for additional MODY relevant genes, such as NKX6-1, and these require further validation.

Identifying and mitigating batch effects in whole genome sequencing data.

BACKGROUND: Large sample sets of whole genome sequencing with deep coverage are being generated, however assembling datasets from different sources inevitably introduces batch effects. These batch effects are not well understood and can be due to changes in the sequencing protocol or bioinformatics tools used to process the data. No systematic algorithms or heuristics exist to detect and filter batch effects or remove associations impacted by batch effects in whole genome sequencing data. RESULTS: We describe key quality metrics, provide a freely available software package to compute them, and demonstrate that identification of batch effects is aided by principal components analysis of these metrics. To mitigate batch effects, we developed new site-specific filters that identified and removed variants that falsely associated with the phenotype due to batch effect. These include filtering based on: a haplotype based genotype correction, a differential genotype quality test, and removing sites with missing genotype rate greater than 30% after setting genotypes with quality scores less than 20 to missing. This method removed 96.1% of unconfirmed genome-wide significant SNP associations and 97.6% of unconfirmed genome-wide significant indel associations. We performed analyses to demonstrate that: 1) These filters impacted variants known to be disease associated as 2 out of 16 confirmed associations in an AMD candidate SNP analysis were filtered, representing a reduction in power of 12.5%, 2) In the absence of batch effects, these filters removed only a small proportion of variants across the genome (type I error rate of 3%), and 3) in an independent dataset, the method removed 90.2% of unconfirmed genome-wide SNP associations and 89.8% of unconfirmed genome-wide indel associations. CONCLUSIONS: Researchers currently do not have effective tools to identify and mitigate batch effects in whole genome sequencing data. We developed and validated methods and filters to address this deficiency.

Cognitive Deficits, Changes in Synaptic Function, and Brain Pathology in a Mouse Model of Normal Aging(1,2,3).

Age is the main risk factor for sporadic Alzheimer's disease. Yet, cognitive decline in aged rodents has been less well studied, possibly due to concomitant changes in sensory or locomotor function that can complicate cognitive tests. We tested mice that were 3, 11, and 23 months old in cognitive, sensory, and motor measures, and postmortem measures of gliosis and neural activity (c-Fos). Hippocampal synaptic function was also examined. While age-related impairments were detectable in tests of spatial memory, greater age-dependent effects were observed in tests of associative learning [active avoidance (AA)]. Gross visual function was largely normal, but startle responses to acoustic stimuli decreased with increased age, possibly due to hearing impairments. Therefore, a novel AA variant in which light alone served as the conditioning stimuli was used. Age-related deficits were again observed. Mild changes in vision, as measured by optokinetic responses, were detected in 19- versus 4-month-old mice, but these were not correlated to AA performance. Thus, deficits in hearing or vision are unlikely to account for the observed deficits in cognitive measures. Increased gliosis was observed in the hippocampal formation at older ages. Age-related changes in neural function and plasticity were observed with decreased c-Fos in the dentate gyrus, and decreased synaptic strength and paired-pulse facilitation in CA1 slices. This work, which carefully outlines age-dependent impairments in cognitive and synaptic function, c-Fos activity, and gliosis during normal aging in the mouse, suggests robust translational measures that will facilitate further study of the biology of aging.

A new large-scale manufacturing platform for complex biopharmaceuticals.

Complex biopharmaceuticals, such as recombinant blood coagulation factors, are addressing critical medical needs and represent a growing multibillion-dollar market. For commercial manufacturing of such, sometimes inherently unstable, molecules it is important to minimize product residence time in non-ideal milieu in order to obtain acceptable yields and consistently high product quality. Continuous perfusion cell culture allows minimization of residence time in the bioreactor, but also brings unique challenges in product recovery, which requires innovative solutions. In order to maximize yield, process efficiency, facility and equipment utilization, we have developed, scaled-up and successfully implemented a new integrated manufacturing platform in commercial scale. This platform consists of a (semi-)continuous cell separation process based on a disposable flow path and integrated with the upstream perfusion operation, followed by membrane chromatography on large-scale adsorber capsules in rapid cycling mode. Implementation of the platform at commercial scale for a new product candidate led to a yield improvement of 40% compared to the conventional process technology, while product quality has been shown to be more consistently high. Over 1,000,000 L of cell culture harvest have been processed with 100% success rate to date, demonstrating the robustness of the new platform process in GMP manufacturing. While membrane chromatography is well established for polishing in flow-through mode, this is its first commercial-scale application for bind/elute chromatography in the biopharmaceutical industry and demonstrates its potential in particular for manufacturing of potent, low-dose biopharmaceuticals.

Does history repeat itself? Wavelets and the phylodynamics of influenza A.

Unprecedented global surveillance of viruses will result in massive sequence data sets that require new statistical methods. These data sets press the limits of Bayesian phylogenetics as the high-dimensional parameters that comprise a phylogenetic tree increase the already sizable computational burden of these techniques. This burden often results in partitioning the data set, for example, by gene, and inferring the evolutionary dynamics of each partition independently, a compromise that results in stratified analyses that depend only on data within a given partition. However, parameter estimates inferred from these stratified models are likely strongly correlated, considering they rely on data from a single data set. To overcome this shortfall, we exploit the existing Monte Carlo realizations from stratified Bayesian analyses to efficiently estimate a nonparametric hierarchical wavelet-based model and learn about the time-varying parameters of effective population size that reflect levels of genetic diversity across all partitions simultaneously. Our methods are applied to complete genome influenza A sequences that span 13 years. We find that broad peaks and trends, as opposed to seasonal spikes, in the effective population size history distinguish individual segments from the complete genome. We also address hypotheses regarding intersegment dynamics within a formal statistical framework that accounts for correlation between segment-specific parameters.

Impact of CCR5delta32 host genetic background and disease progression on HIV-1 intrahost evolutionary processes: efficient hypothesis testing through hierarchical phylogenetic models.

The interplay between C-C chemokine receptor type 5 (CCR5) host genetic background, disease progression, and intrahost HIV-1 evolutionary dynamics remains unclear because differences in viral evolution between hosts limit the ability to draw conclusions across hosts stratified into clinically relevant populations. Similar inference problems are proliferating across many measurably evolving pathogens for which intrahost sequence samples are readily available. To this end, we propose novel hierarchical phylogenetic models (HPMs) that incorporate fixed effects to test for differences in dynamics across host populations in a formal statistical framework employing stochastic search variable selection and model averaging. To clarify the role of CCR5 host genetic background and disease progression on viral evolutionary patterns, we obtain gp120 envelope sequences from clonal HIV-1 variants isolated at multiple time points in the course of infection from populations of HIV-1-infected individuals who only harbored CCR5-using HIV-1 variants at all time points. Presence or absence of a CCR5 wt/Δ32 genotype and progressive or long-term nonprogressive course of infection stratify the clinical populations in a two-way design. As compared with the standard approach of analyzing sequences from each patient independently, the HPM provides more efficient estimation of evolutionary parameters such as nucleotide substitution rates and d(N)/d(S) rate ratios, as shown by significant shrinkage of the estimator variance. The fixed effects also correct for nonindependence of data between populations and results in even further shrinkage of individual patient estimates. Model selection suggests an association between nucleotide substitution rate and disease progression, but a role for CCR5 genotype remains elusive. Given the absence of clear d(N)/d(S) differences between patient groups, delayed onset of AIDS symptoms appears to be solely associated with lower viral replication rates rather than with differences in selection on amino acid fixation.

Reuse, Recycle, Reweigh: Combating Influenza through Efficient Sequential Bayesian Computation for Massive Data.

Massive datasets in the gigabyte and terabyte range combined with the availability of increasingly sophisticated statistical tools yield analyses at the boundary of what is computationally feasible. Compromising in the face of this computational burden by partitioning the dataset into more tractable sizes results in stratified analyses, removed from the context that justified the initial data collection. In a Bayesian framework, these stratified analyses generate intermediate realizations, often compared using point estimates that fail to account for the variability within and correlation between the distributions these realizations approximate. However, although the initial concession to stratify generally precludes the more sensible analysis using a single joint hierarchical model, we can circumvent this outcome and capitalize on the intermediate realizations by extending the dynamic iterative reweighting MCMC algorithm. In doing so, we reuse the available realizations by reweighting them with importance weights, recycling them into a now tractable joint hierarchical model. We apply this technique to intermediate realizations generated from stratified analyses of 687 influenza A genomes spanning 13 years allowing us to revisit hypotheses regarding the evolutionary history of influenza within a hierarchical statistical framework.

Protein microarrays guide tolerizing DNA vaccine treatment of autoimmune encephalomyelitis.

The diversity of autoimmune responses poses a formidable challenge to the development of antigen-specific tolerizing therapy. We developed 'myelin proteome' microarrays to profile the evolution of autoantibody responses in experimental autoimmune encephalomyelitis (EAE), a model for multiple sclerosis (MS). Increased diversity of autoantibody responses in acute EAE predicted a more severe clinical course. Chronic EAE was associated with previously undescribed extensive intra- and intermolecular epitope spreading of autoreactive B-cell responses. Array analysis of autoantigens targeted in acute EAE was used to guide the choice of autoantigen cDNAs to be incorporated into expression plasmids so as to generate tolerizing vaccines. Tolerizing DNA vaccines encoding a greater number of array-determined myelin targets proved superior in treating established EAE and reduced epitope spreading of autoreactive B-cell responses. Proteomic monitoring of autoantibody responses provides a useful approach to monitor autoimmune disease and to develop and tailor disease- and patient-specific tolerizing DNA vaccines.