Incident heart failure in chronic kidney disease: proteomics informs biology and risk stratification

BACKGROUND AND AIMS

Incident heart failure (HF) among individuals with chronic kidney disease (CKD) incurs hospitalizations that burden patients and health care systems. There are few preventative therapies, and the Pooled Cohort equations to Prevent Heart Failure (PCP-HF) perform poorly in the setting of CKD. New drug targets and better risk stratification are urgently needed.

METHODS

In this analysis of incident HF, SomaScan V4.0 (4638 proteins) was analysed in 2906 participants of the Chronic Renal Insufficiency Cohort (CRIC) with validation in the Atherosclerosis Risk in Communities (ARIC) study. The primary outcome was 14-year incident HF (390 events); secondary outcomes included 4-year HF (183 events), HF with reduced ejection fraction (137 events), and HF with preserved ejection fraction (165 events). Mendelian randomization and Gene Ontology were applied to examine causality and pathways. The performance of novel multi-protein risk models was compared to the PCP-HF risk score.

RESULTS

Over 200 proteins were associated with incident HF after adjustment for estimated glomerular filtration rate at P < 1 × 10-5. After adjustment for covariates including N-terminal pro-B-type natriuretic peptide, 17 proteins remained associated at P < 1 × 10-5. Mendelian randomization associations were found for six proteins, of which four are druggable targets: FCG2B, IGFBP3, CAH6, and ASGR1. For the primary outcome, the C-statistic (95% confidence interval [CI]) for the 48-protein model in CRIC was 0.790 (0.735, 0.844) vs. 0.703 (0.644, 0.762) for the PCP-HF model (P = .001). C-statistic (95% CI) for the protein model in ARIC was 0.747 (0.707, 0.787).

CONCLUSIONS

Large-scale proteomics reveal novel circulating protein biomarkers and potential mediators of HF in CKD. Proteomic risk models improve upon the PCP-HF risk score in this population.

Proteomics of CKD progression in the chronic renal insufficiency cohort

Progression of chronic kidney disease (CKD) portends myriad complications, including kidney failure. In this study, we analyze associations of 4638 plasma proteins among 3235 participants of the Chronic Renal Insufficiency Cohort Study with the primary outcome of 50% decline in estimated glomerular filtration rate or kidney failure over 10 years. We validate key findings in the Atherosclerosis Risk in the Communities study. We identify 100 circulating proteins that are associated with the primary outcome after multivariable adjustment, using a Bonferroni statistical threshold of significance. Individual protein associations and biological pathway analyses highlight the roles of bone morphogenetic proteins, ephrin signaling, and prothrombin activation. A 65-protein risk model for the primary outcome has excellent discrimination (C-statistic[95%CI] 0.862 [0.835, 0.889]), and 14/65 proteins are druggable targets. Potentially causal associations for five proteins, to our knowledge not previously reported, are supported by Mendelian randomization: EGFL9, LRP-11, MXRA7, IL-1 sRII and ILT-2. Modifiable protein risk markers can guide therapeutic drug development aimed at slowing CKD progression.

Assessing chromatin relocalization in 3D using the patient rule induction method

Three-dimensional (3D) genome architecture is critical for numerous cellular processes, including transcription, while certain conformation-driven structural alterations are frequently oncogenic. Inferring 3D chromatin configurations has been advanced by the emergence of chromatin conformation capture assays, notably Hi-C, and attendant 3D reconstruction algorithms. These have enhanced understanding of chromatin spatial organization and afforded numerous downstream biological insights. Until recently, comparisons of 3D reconstructions between conditions and/or cell types were limited to prescribed structural features. However, multiMDS, a pioneering approach developed by Rieber and Mahony (2019). that performs joint reconstruction and alignment, enables quantification of all locus-specific differences between paired Hi-C data sets. By subsequently mapping these differences to the linear (1D) genome the identification of relocalization regions is facilitated through the use of peak calling in conjunction with continuous wavelet transformation. Here, we seek to refine this approach by performing the search for significant relocalization regions in terms of the 3D structures themselves, thereby retaining the benefits of 3D reconstruction and avoiding limitations associated with the 1D perspective. The search for (extreme) relocalization regions is conducted using the patient rule induction method (PRIM). Considerations surrounding orienting structures with respect to compartmental and principal component axes are discussed, as are approaches to inference and reconstruction accuracy assessment. The illustration makes recourse to comparisons between four different cell types.

Proteomic cardiovascular risk assessment in chronic kidney disease

AIMS

Chronic kidney disease (CKD) is widely prevalent and independently increases cardiovascular risk. Cardiovascular risk prediction tools derived in the general population perform poorly in CKD. Through large-scale proteomics discovery, this study aimed to create more accurate cardiovascular risk models.

METHODS AND RESULTS

Elastic net regression was used to derive a proteomic risk model for incident cardiovascular risk in 2182 participants from the Chronic Renal Insufficiency Cohort. The model was then validated in 485 participants from the Atherosclerosis Risk in Communities cohort. All participants had CKD and no history of cardiovascular disease at study baseline when ∼5000 proteins were measured. The proteomic risk model, which consisted of 32 proteins, was superior to both the 2013 ACC/AHA Pooled Cohort Equation and a modified Pooled Cohort Equation that included estimated glomerular filtrate rate. The Chronic Renal Insufficiency Cohort internal validation set demonstrated annualized receiver operating characteristic area under the curve values from 1 to 10 years ranging between 0.84 and 0.89 for the protein and 0.70 and 0.73 for the clinical models. Similar findings were observed in the Atherosclerosis Risk in Communities validation cohort. For nearly half of the individual proteins independently associated with cardiovascular risk, Mendelian randomization suggested a causal link to cardiovascular events or risk factors. Pathway analyses revealed enrichment of proteins involved in immunologic function, vascular and neuronal development, and hepatic fibrosis.

CONCLUSION

In two sizeable populations with CKD, a proteomic risk model for incident cardiovascular disease surpassed clinical risk models recommended in clinical practice, even after including estimated glomerular filtration rate. New biological insights may prioritize the development of therapeutic strategies for cardiovascular risk reduction in the CKD population.

Analytical and Biological Variability of a Commercial Modified Aptamer Assay in Plasma Samples of Patients with Chronic Kidney Disease

BACKGROUND

We carried out a study of the aptamer proteomic assay, SomaScan V4, to evaluate the analytical and biological variability of the assay in plasma samples of patients with moderate to severe chronic kidney disease (CKD).

METHODS

Plasma samples were selected from 2 sources: (a) 24 participants from the Chronic Renal Insufficiency Cohort (CRIC) and (b) 49 patients from the Brigham and Women's Hospital-Kidney/Renal Clinic. We calculated intra-assay variability from both sources and examined short-term biological variability in samples from the Brigham clinic. We also measured correlations of aptamer measurements with traditional biomarker assays.

RESULTS

A total of 4656 unique proteins (4849 total aptamer measures) were analyzed in all samples. Median (interquartile range [IQR] intra-assay CV) was 3.7% (2.8-5.3) in CRIC and 5.0% (3.8-7.0) in Brigham samples. Median (IQR) biological CV among Brigham samples drawn from one individual on 2 occasions separated by median (IQR) 7 (4-14) days was 8.7% (6.2-14). CVs were independent of CKD stage, diabetes, or albuminuria but were higher in patients with systemic lupus erythematosus. Rho correlations between aptamer and traditional assays for biomarkers of interest were cystatin C = 0.942, kidney injury model-1 = 0.905, fibroblast growth factor-23 = 0.541, tumor necrosis factor receptors 1 = 0.781 and 2 = 0.843, P < 10-100 for all.

CONCLUSIONS

Intra-assay and within-subject variability for SomaScan in the CKD setting was low and similar to assay variability reported from individuals without CKD. Intra-assay precision was excellent whether samples were collected in an optimal research protocol, as were CRIC samples, or in the clinical setting, as were the Brigham samples.

Does multi-way, long-range chromatin contact data advance 3D genome reconstruction?

BACKGROUND

Methods for inferring the three-dimensional (3D) configuration of chromatin from conformation capture assays that provide strictly pairwise interactions, notably Hi-C, utilize the attendant contact matrix as input. More recent assays, in particular split-pool recognition of interactions by tag extension (SPRITE), capture multi-way interactions instead of solely pairwise contacts. These assays yield contacts that straddle appreciably greater genomic distances than Hi-C, in addition to instances of exceptionally high-order chromatin interaction. Such attributes are anticipated to be consequential with respect to 3D genome reconstruction, a task yet to be undertaken with multi-way contact data. However, performing such 3D reconstruction using distance-based reconstruction techniques requires framing multi-way contacts as (pairwise) distances. Comparing approaches for so doing, and assessing the resultant impact of long-range and multi-way contacts, are the objectives of this study.

RESULTS

We obtained 3D reconstructions via multi-dimensional scaling under a variety of weighting schemes for mapping SPRITE multi-way contacts to pairwise distances. Resultant configurations were compared following Procrustes alignment and relationships were assessed between associated Procrustes root mean square errors and key features such as the extent of multi-way and/or long-range contacts. We found that these features had surprisingly limited influence on 3D reconstruction, a finding we attribute to their influence being diminished by the preponderance of pairwise contacts.

CONCLUSION

Distance-based 3D genome reconstruction using SPRITE multi-way contact data is not appreciably affected by the weighting scheme used to convert multi-way interactions to pairwise distances.

Increased rates of secondary bacterial infections, including Enterococcus bacteremia, in patients hospitalized with coronavirus disease 2019 (COVID-19)

OBJECTIVE

We compared the rates of hospital-onset secondary bacterial infections in patients with coronavirus disease 2019 (COVID-19) with rates in patients with influenza and controls, and we investigated reports of increased incidence of Enterococcus infections in patients with COVID-19.

DESIGN

Retrospective cohort study.

SETTING

An academic quaternary-care hospital in San Francisco, California.

PATIENTS

Patients admitted between October 1, 2019, and October 1, 2020, with a positive SARS-CoV-2 PCR (N = 314) or influenza PCR (N = 82) within 2 weeks of admission were compared with inpatients without positive SARS-CoV-2 or influenza tests during the study period (N = 14,332).

METHODS

National Healthcare Safety Network definitions were used to identify infection-related ventilator-associated complications (IVACs), probable ventilator-associated pneumonia (PVAP), bloodstream infections (BSIs), and catheter-associated urinary tract infections (CAUTIs). A multiple logistic regression model was used to control for likely confounders.

RESULTS

COVID-19 patients had significantly higher rates of IVAC and PVAP compared to controls, with adjusted odds ratios of 4.7 (95% confidence interval [CI], 1.7-13.9) and 10.4 (95 % CI, 2.1-52.1), respectively. COVID-19 patients had higher incidence of BSI due to Enterococcus but not BSI generally, and whole-genome sequencing of Enterococcus isolates demonstrated that nosocomial transmission did not explain the increased rate. Subanalyses of patients admitted to the intensive care unit and patients who required mechanical ventilation revealed similar findings.

CONCLUSIONS

COVID-19 is associated with an increased risk of IVAC, PVAP, and Enterococcus BSI compared with hospitalized controls, which is not fully explained by factors such as immunosuppressive treatments and duration of mechanical ventilation. The mechanism underlying increased rates of Enterococcus BSI in COVID-19 patients requires further investigation.

Can 3D diploid genome reconstruction from unphased Hi-C data be salvaged?

The three-dimensional (3D) configuration of chromatin impacts numerous cellular processes. However, directly observing chromatin architecture at high resolution is challenging. Accordingly, inferring 3D structure utilizing chromatin conformation capture assays, notably Hi-C, has received considerable attention, with a multitude of reconstruction algorithms advanced. While these have enhanced appreciation of chromatin organization, most suffer from a serious shortcoming when faced with diploid genomes: inability to disambiguate contacts between corresponding loci on homologous chromosomes, making attendant reconstructions potentially meaningless. Three recent proposals offer a computational way forward at the expense of strong assumptions. Here, we show that making plausible assumptions about the components of homologous chromosome contacts provides a basis for rescuing conventional consensus-based, unphased reconstruction. This would be consequential since not only are assumptions needed for diploid reconstruction considerable, but the sophistication of select unphased algorithms affords substantive advantages with regard resolution and folding complexity. Rather than presuming that the requisite salvaging assumptions are met, we exploit a recent imaging technology, in situ genome sequencing (IGS), to comprehensively evaluate their reasonableness. We analogously use IGS to assess assumptions underpinning diploid reconstruction algorithms. Results convincingly demonstrate that, in all instances, assumptions are not met, making further algorithm development, potentially informed by IGS data, essential.

Indoor Air Pollution and Susceptibility to Tuberculosis Infection in Urban Vietnamese Children

RATIONALE

The Southeast Asian tuberculosis burden is high, and it remains unclear if urban indoor air pollution in this setting is exacerbating the epidemic.

OBJECTIVES

To determine the associations of latent tuberculosis with common urban indoor air pollution sources (secondhand smoke, indoor motorcycle emissions, and cooking) in Southeast Asia.

METHODS

We enrolled child household contacts of patients with microbiologically confirmed active tuberculosis in Vietnam, July 2017-December 2019. We tested children for latent tuberculosis and evaluated air pollution exposures with questionnaires and personal aerosol sampling. We tested hypotheses using generalized estimating equations.

MEASUREMENTS AND MAIN RESULTS

We enrolled 72 tuberculosis patients (27% with cavitary disease) and 109 of their child household contacts. Of household contacts, 58 (53%) were diagnosed with latent tuberculosis at baseline visit. Children experienced a 2.56-fold increased odds of latent tuberculosis for each additional household member who smoked (95%CI 1.27-5.16). Odds were highest among children exposed to indoor smokers and children under five years old exposed to household smokers. Each residential floor above street-level pollution decreased the odds of latent tuberculosis by 36% (aOR 0.64, 95%CI 0.42-0.96). Motorcycles parked inside children's homes and cooking with liquid petroleum gas compared to electricity increased the odds of latent tuberculosis while kitchen ventilation decreased the effect, but these findings were not statistically significant.

CONCLUSION

Common urban indoor air pollution sources were associated with increased odds of latent tuberculosis infection in child household contacts of active tuberculosis patients.

Machine intelligence identifies soluble TNFa as a therapeutic target for spinal cord injury

Traumatic spinal cord injury (SCI) produces a complex syndrome that is expressed across multiple endpoints ranging from molecular and cellular changes to functional behavioral deficits. Effective therapeutic strategies for CNS injury are therefore likely to manifest multi-factorial effects across a broad range of biological and functional outcome measures. Thus, multivariate analytic approaches are needed to capture the linkage between biological and neurobehavioral outcomes. Injury-induced neuroinflammation (NI) presents a particularly challenging therapeutic target, since NI is involved in both degeneration and repair. Here, we used big-data integration and large-scale analytics to examine a large dataset of preclinical efficacy tests combining five different blinded, fully counter-balanced treatment trials for different acute anti-inflammatory treatments for cervical spinal cord injury in rats. Multi-dimensional discovery, using topological data analysis (TDA) and principal components analysis (PCA) revealed that only one showed consistent multidimensional syndromic benefit: intrathecal application of recombinant soluble TNFα receptor 1 (sTNFR1), which showed an inverse-U dose response efficacy. Using the optimal acute dose, we showed that clinically-relevant 90 min delayed treatment profoundly affected multiple biological indices of NI in the first 48 h after injury, including reduction in pro-inflammatory cytokines and gene expression of a coherent complex of acute inflammatory mediators and receptors. Further, a 90 min delayed bolus dose of sTNFR1 reduced the expression of NI markers in the chronic perilesional spinal cord, and consistently improved neurological function over 6 weeks post SCI. These results provide validation of a novel strategy for precision preclinical drug discovery that is likely to improve translation in the difficult landscape of CNS trauma, and confirm the importance of TNFα signaling as a therapeutic target.

Composition and origin of lung fluid proteome in premature infants and relationship to respiratory outcome

Background

Infants born at extremely low gestational age are at high risk for bronchopulmonary dysplasia and continuing lung disease. There are no early clinical biomarkers for pulmonary outcome and limited therapeutic interventions.

Objectives

We performed global proteomics of premature infant tracheal aspirate (TA) and plasma to determine the composition and source of lung fluid proteins and to identify potential biomarkers of respiratory outcome.

Methods

TA samples were collected from intubated infants in the TOLSURF cohort before and after nitric oxide treatment, and plasma was collected from NO CLD infants. Protein abundance was assayed by HPLC/tandem mass spectrometry and Protein Prospector software. mRNA abundance in mid-gestation fetal lung was assessed by RNA sequencing. Pulmonary morbidity was defined as a need for ventilatory support at term and during the first year.

Results

Abundant TA proteins included albumin, hemoglobin, and actin-related proteins. 96 of 137 detected plasma proteins were present in TA (r = 0.69, p<0.00001). Based on lung RNAseq data, ~88% of detected TA proteins in injured infant lung are derived at least in part from lung epithelium with overrepresentation in categories of cell membrane/secretion and stress/inflammation. Comparing 37 infants at study enrollment (7–14 days) who did or did not develop persistent pulmonary morbidity, candidate biomarkers of both lung (eg., annexin A5) and plasma (eg., vitamin D-binding protein) origin were identified. Notably, levels of free hemoglobin were 2.9-fold (p = 0.03) higher in infants with pulmonary morbidity. In time course studies, hemoglobin decreased markedly in most infants after enrollment coincident with initiation of inhaled nitric oxide treatment.

Conclusions

We conclude that both lung epithelium and plasma contribute to the lung fluid proteome in premature infants with lung injury. Early postnatal elevation of free hemoglobin and heme, which are both pro-oxidants, may contribute to persistent lung disease by depleting nitric oxide and increasing oxidative/nitrative stress.

Correlates and Consequences of High Serum Irisin Concentration in Patients on Hemodialysis: A Longitudinal Analysis

OBJECTIVE

Irisin is a hormone released by muscle in response to exercise that acts on white adipose cells to stimulate browning of adipose tissue. We aimed to examine irisin correlates and consequences of irisin in patients receiving hemodialysis.

DESIGN AND METHODS

A prospective cohort study was conducted using data from 749 prevalent patients receiving hemodialysis. Multivariable linear regression and multivariable generalized estimating equations were used to determine correlates of baseline and change in serum irisin concentration. Proportional hazards (Cox) regression was used to assess the association between serum irisin concentration and time to death.

RESULTS

Age and body mass index were inversely associated with baseline and change in serum irisin concentration. Lower muscle mass as estimated by serum creatinine concentration was associated with lower irisin concentration (-1.38% per mg/dL (95% confidence interval [CI]: -2.45, -0.21) and with a 0.72% decrease in irisin concentration (95% CI: -1.48, -0.04) from baseline to 12 months. Each 50% higher serum interleukin-6 (IL-6) concentration was associated with 1.52% higher serum irisin concentration (95% CI: 0.38, 2.66) at baseline and an increase of 1.04% in irisin concentration over 1 year (95% CI: 0.47, 1.61). Irisin concentration at baseline was associated with higher hazard of death (hazards ratio: 1.45, 95% CI: 1.05 2.00); an increase in irisin concentration over 1 year was associated with a higher hazard of death (hazards ratio: 1.34, 95% CI: 1.01, 1.79). In formal mediation analysis, serum IL-6 was a mediator in the association between serum irisin and mortality.

CONCLUSIONS

Lower serum creatinine (reflecting lower muscle mass) and higher serum IL-6 were associated with higher serum irisin concentrations. Higher serum irisin concentrations were associated with higher mortality, which may be mediated by inflammation.

Principal curve approaches for inferring 3D chromatin architecture

Three-dimensional (3D) genome spatial organization is critical for numerous cellular processes, including transcription, while certain conformation-driven structural alterations are frequently oncogenic. Genome architecture had been notoriously difficult to elucidate, but the advent of the suite of chromatin conformation capture assays, notably Hi-C, has transformed understanding of chromatin structure and provided downstream biological insights. Although many findings have flowed from direct analysis of the pairwise proximity data produced by these assays, there is added value in generating corresponding 3D reconstructions deriving from superposing genomic features on the reconstruction. Accordingly, many methods for inferring 3D architecture from proximity data have been advanced. However, none of these approaches exploit the fact that single chromosome solutions constitute a one-dimensional (1D) curve in 3D. Rather, this aspect has either been addressed by imposition of constraints, which is both computationally burdensome and cell type specific, or ignored with contiguity imposed after the fact. Here, we target finding a 1D curve by extending principal curve methodology to the metric scaling problem. We illustrate how this approach yields a sequence of candidate solutions, indexed by an underlying smoothness or degrees-of-freedom parameter, and propose methods for selection from this sequence. We apply the methodology to Hi-C data obtained on IMR90 cells and so are positioned to evaluate reconstruction accuracy by referencing orthogonal imaging data. The results indicate the utility and reproducibility of our principal curve approach in the face of underlying structural variation.

Assessing stationary distributions derived from chromatin contact maps

Background

The spatial configuration of chromosomes is essential to various cellular processes, notably gene regulation, while architecture related alterations, such as translocations and gene fusions, are often cancer drivers. Thus, eliciting chromatin conformation is important, yet challenging due to compaction, dynamics and scale. However, a variety of recent assays, in particular Hi-C, have generated new details of chromatin structure, spawning a number of novel biological findings. Many findings have resulted from analyses on the level of native contact data as generated by the assays. Alternatively, reconstruction based approaches often proceed by first converting contact frequencies into distances, then generating a three dimensional (3D) chromatin configuration that best recapitulates these distances. Subsequent analyses can enrich contact level analyses via superposition of genomic attributes on the reconstruction. But, such advantages depend on the accuracy of the reconstruction which, absent gold standards, is inherently difficult to assess. Attempts at accuracy evaluation have relied on simulation and/or FISH imaging that typically features a handful of low resolution probes. While newly advanced multiplexed FISH imaging offers possibilities for refined 3D reconstruction accuracy evaluation, availability of such data is limited due to assay complexity and the resolution thereof is appreciably lower than the reconstructions being assessed. Accordingly, there is demand for new methods of reconstruction accuracy appraisal.

Results

Here we explore the potential of recently proposed stationary distributions, hereafter StatDns, derived from Hi-C contact matrices, to serve as a basis for reconstruction accuracy assessment. Current usage of such StatDns has focussed on the identification of highly interactive regions (HIRs): computationally defined regions of the genome purportedly involved in numerous long-range intra-chromosomal contacts. Consistent identification of HIRs would be informative with respect to inferred 3D architecture since the corresponding regions of the reconstruction would have an elevated number of k nearest neighbors (kNNs). More generally, we anticipate a monotone decreasing relationship between StatDn values and kNN distances. After initially evaluating the reproducibility of StatDns across replicate Hi-C data sets, we use this implied StatDn - kNN relationship to gauge the utility of StatDns for reconstruction validation, making recourse to both real and simulated examples.

Conclusions

Our analyses demonstrate that, as constructed, StatDns do not provide a suitable measure for assessing the accuracy of 3D genome reconstructions. Whether this is attributable to specific choices surrounding normalization in defining StatDns or to the logic underlying their very formulation remains to be determined.

Epigenomic profiling of newborns with isolated orofacial clefts reveals widespread DNA methylation changes and implicates metastable epiallele regions in disease risk

Cleft lip with or without cleft palate (CL/P) is a common human birth defect whose etiologies remain largely unknown. Several studies have demonstrated that periconceptional supplementation of folic acid can reduce risk of CL/P in offspring. In this study, we tested the hypothesis that the preventive effect of folic acid is manifested through epigenetic modifications by determining whether DNA methylation changes are associated with CL/P. To more readily observe the potential effects of maternal folate on the offspring epigenome, we focused on births prior to mandatory dietary folate fortification in the United States (i.e. birth year 1997 or earlier). Genomic DNA methylation levels were assessed from archived newborn bloodspots in a 182-member case-control study using the Illumina® Human Beadchip 450K array. CL/P cases displayed striking epigenome-wide hypomethylation relative to controls: 63% of CpGs interrogated had lower methylation levels in case newborns, a trend which held up in racially stratified sub-groups. 28 CpG sites reached epigenome-wide significance and all were case-hypomethylated. The most significant CL/P-associated differentially methylated region encompassed the VTRNA2-1 gene, which was also hypomethylated in cases (FWER p = 0.014). This region has been previously characterized as a nutritionally-responsive, metastable epiallele and CL/P-associated methylation changes, in general, were greater at or near putative metastable epiallelic regions. Gene Set Enrichment Analysis of CL/P-associated DMRs showed an over-representation of genes involved in palate development such as WNT9B, MIR140 and LHX8. CL/P-associated DNA methylation changes may partly explain the mechanism by which orofacial clefts are responsive to maternal folate levels.

Frailty Among Patients Receiving Hemodialysis: Evolution of Components and Associations With Mortality

BACKGROUND

Understanding how components of frailty change over time and how they can be modeled as time-dependent predictors of mortality could lead to better risk prediction in the dialysis population.

METHODS

We measured frailty at baseline, 12 months, and 24 months among 727 patients receiving hemodialysis in Northern California and Atlanta. We examined the likelihood of meeting frailty components (weight loss, exhaustion, low physical activity, weak grip strength, and slow gait speed) as a function of time in logistic regression analysis and association of frailty components with mortality in time-updated multivariable Cox models.

RESULTS

Physical activity and gait speed declined, exhaustion and grip strength did not change, and the odds of meeting the weight loss criterion declined with time. All five components were associated with higher mortality in multivariable analyses, but gait speed was the strongest individual predictor. All frailty components except physical inactivity were independently associated with mortality when all five components were included in the same model. The number of frailty components met was associated with mortality in a gradient that ranged from a hazard ratio of 2.73 for one component to 10.07 for five components met; the model including all five components was the best model based on Akaike information criterion.

CONCLUSIONS

Measurement of all frailty components was necessary for optimal mortality prediction, and the number of components met was strongly associated with mortality in this cohort.

Surfactant status and respiratory outcome in premature infants receiving late surfactant treatment

BACKGROUND

Many premature infants with respiratory failure are deficient in surfactant, but the relationship to occurrence of bronchopulmonary dysplasia (BPD) is uncertain.

METHODS

Tracheal aspirates were collected from 209 treated and control infants enrolled at 7-14 days in the Trial of Late Surfactant. The content of phospholipid, surfactant protein B, and total protein were determined in large aggregate (active) surfactant.

RESULTS

At 24 h, surfactant treatment transiently increased surfactant protein B content (70%, p < 0.01), but did not affect recovered airway surfactant or total protein/phospholipid. The level of recovered surfactant during dosing was directly associated with content of surfactant protein B (r = 0.50, p < 0.00001) and inversely related to total protein (r = 0.39, p < 0.0001). For all infants, occurrence of BPD was associated with lower levels of recovered large aggregate surfactant, higher protein content, and lower SP-B levels. Tracheal aspirates with lower amounts of recovered surfactant had an increased proportion of small vesicle (inactive) surfactant.

CONCLUSIONS

We conclude that many intubated premature infants are deficient in active surfactant, in part due to increased intra-alveolar metabolism, low SP-B content, and protein inhibition, and that the severity of this deficit is predictive of BPD. Late surfactant treatment at the frequency used did not provide a sustained increase in airway surfactant.

Improved accuracy assessment for 3D genome reconstructions

Background

Three dimensional (3D) genome spatial organization is critical for numerous cellular functions, including transcription, while certain conformation-driven structural alterations are frequently oncogenic. Genome conformation had been difficult to elucidate but the advent chromatin conformation capture assays, notably Hi-C, has transformed understanding of chromatin architecture and yielded numerous biological insights. Although most of these findings have flowed from analysis of proximity data produced by these assays, added value in generating 3D reconstructions has been demonstrated, deriving, in part, from superposing genomic features on the reconstruction. However, advantages of 3D structure-based analyses are clearly conditional on the accuracy of the attendant reconstructions, which is difficult to assess. Proponents of competing reconstruction algorithms have evaluated their accuracy by recourse to simulation of toy structures and/or limited fluorescence in situ hybridization (FISH) imaging that features a handful of low resolution probes. Accordingly, new methods of reconstruction accuracy assessment are needed.

Results

Here we utilize two recently devised assays to develop methodology for assessing 3D reconstruction accuracy. Multiplex FISH increases the number of probes by an order of magnitude and hence the number of inter-probe distances by two orders, providing sufficient information for structure-level evaluation via mean-squared deviations (MSD). Crucially, underscoring multiplex FISH applications are large numbers of coordinate-system aligned replicates that provide the basis for a referent distribution for MSD statistics. Using this system we show that reconstructions based on Hi-C data for IMR90 cells are accurate for some chromosomes but not others. The second new assay, genome architecture mapping, utilizes large numbers of thin cryosections to obtain a measure of proximity. We exploit the planarity of the cryosections – not used in inferring proximity – to obtain measures of reconstruction accuracy, with referents provided via resampling. Application to mouse embryonic stem cells shows reconstruction accuracies that vary by chromosome.

Conclusions

We have developed methods for assessing the accuracy of 3D genome reconstructions that exploit features of recently advanced multiplex FISH and genome architecture mapping assays. These approaches can help overcome the absence of gold standards for making such assessments which are important in view of the considerable uncertainties surrounding 3D genome reconstruction.

Memory T Cell Proliferation before Hepatitis C Virus Therapy Predicts Antiviral Immune Responses and Treatment Success

The contribution of the host immune system to the efficacy of new anti-hepatitis C virus (HCV) drugs is unclear. We undertook a longitudinal prospective study of 33 individuals with chronic HCV treated with combination pegylated IFN-α, ribavirin, and telaprevir/boceprevir. We characterized innate and adaptive immune cells to determine whether kinetics of the host response could predict sustained virologic response (SVR). We show that characteristics of the host immune system present before treatment were correlated with successful therapy. Augmentation of adaptive immune responses during therapy was more impressive among those achieving SVR. Most importantly, active memory T cell proliferation before therapy predicted SVR and was associated with the magnitude of the HCV-specific responses at week 12 after treatment start. After therapy initiation, the most important correlate of success was minimal monocyte activation, as predicted by previous in vitro work. In addition, subjects achieving SVR had increasing expression of the transcription factor T-bet, a driver of Th1 differentiation and cytotoxic effector cell maturation. These results show that host immune features present before treatment initiation predict SVR and eventual development of a higher frequency of functional virus-specific cells in blood. Such host characteristics may also be required for successful vaccine-mediated protection.

Biomarkers of Tuberculosis Severity and Treatment Effect: A Directed Screen of 70 Host Markers in a Randomized Clinical Trial

More efficacious treatment regimens are needed for tuberculosis, however, drug development is impeded by a lack of reliable biomarkers of disease severity and of treatment effect. We conducted a directed screen of host biomarkers in participants enrolled in a tuberculosis clinical trial to address this need. Serum samples from 319 protocol-correct, culture-confirmed pulmonary tuberculosis patients treated under direct observation as part of an international, phase 2 trial were screened for 70 markers of infection, inflammation, and metabolism. Biomarker assays were specifically developed for this study and quantified using a novel, multiplexed electrochemiluminescence assay. We evaluated the association of biomarkers with baseline characteristics, as well as with detailed microbiologic data, using Bonferroni-adjusted, linear regression models. Across numerous analyses, seven proteins, SAA1, PCT, IL-1β, IL-6, CRP, PTX-3 and MMP-8, showed recurring strong associations with markers of baseline disease severity, smear grade and cavitation; were strongly modulated by tuberculosis treatment; and had responses that were greater for patients who culture-converted at 8weeks. With treatment, all proteins decreased, except for osteocalcin, MCP-1 and MCP-4, which significantly increased. Several previously reported putative tuberculosis-associated biomarkers (HOMX1, neopterin, and cathelicidin) were not significantly associated with treatment response. In conclusion, across a geographically diverse and large population of tuberculosis patients enrolled in a clinical trial, several previously reported putative biomarkers were not significantly associated with treatment response, however, seven proteins had recurring strong associations with baseline radiographic and microbiologic measures of disease severity, as well as with early treatment response, deserving additional study.

Improving Assessment of Drug Safety Through Proteomics: Early Detection and Mechanistic Characterization of the Unforeseen Harmful Effects of Torcetrapib

Supplemental Digital Content is available in the text.

Background:

Early detection of adverse effects of novel therapies and understanding of their mechanisms could improve the safety and efficiency of drug development. We have retrospectively applied large-scale proteomics to blood samples from ILLUMINATE (Investigation of Lipid Level Management to Understand its Impact in Atherosclerotic Events), a trial of torcetrapib (a cholesterol ester transfer protein inhibitor), that involved 15 067 participants at high cardiovascular risk. ILLUMINATE was terminated at a median of 550 days because of significant absolute increases of 1.2% in cardiovascular events and 0.4% in mortality with torcetrapib. The aims of our analysis were to determine whether a proteomic analysis might reveal biological mechanisms responsible for these harmful effects and whether harmful effects of torcetrapib could have been detected early in the ILLUMINATE trial with proteomics.

Methods:

A nested case-control analysis of paired plasma samples at baseline and at 3 months was performed in 249 participants assigned to torcetrapib plus atorvastatin and 223 participants assigned to atorvastatin only. Within each treatment arm, cases with events were matched to controls 1:1. Main outcomes were a survey of 1129 proteins for discovery of biological pathways altered by torcetrapib and a 9-protein risk score validated to predict myocardial infarction, stroke, heart failure, or death.

Results:

Plasma concentrations of 200 proteins changed significantly with torcetrapib. Their pathway analysis revealed unexpected and widespread changes in immune and inflammatory functions, as well as changes in endocrine systems, including in aldosterone function and glycemic control. At baseline, 9-protein risk scores were similar in the 2 treatment arms and higher in participants with subsequent events. At 3 months, the absolute 9-protein derived risk increased in the torcetrapib plus atorvastatin arm compared with the atorvastatin-only arm by 1.08% (P=0.0004). Thirty-seven proteins changed in the direction of increased risk of 49 proteins previously associated with cardiovascular and mortality risk.

Conclusions:

Heretofore unknown effects of torcetrapib were revealed in immune and inflammatory functions. A protein-based risk score predicted harm from torcetrapib within just 3 months. A protein-based risk assessment embedded within a large proteomic survey may prove to be useful in the evaluation of therapies to prevent harm to patients.

Clinical Trial Registration:

URL: https://www.clinicaltrials.gov. Unique identifier: NCT00134264.

Traffic-Related Air Pollution and All-Cause Mortality during Tuberculosis Treatment in California

BACKGROUND

Ambient air pollution and tuberculosis (TB) have an impact on public health worldwide, yet associations between the two remain uncertain.

OBJECTIVE

We determined the impact of residential traffic on mortality during treatment of active TB.

METHODS

From 2000-2012, we enrolled 32,875 patients in California with active TB and followed them throughout treatment. We obtained patient data from the California Tuberculosis Registry and calculated traffic volumes and traffic densities in 100- to 400-m radius buffers around residential addresses. We used Cox models to determine mortality hazard ratios, controlling for demographic, socioeconomic, and clinical potential confounders. We categorized traffic exposures as quintiles and determined trends using Wald tests.

RESULTS

Participants contributed 22,576 person-years at risk. There were 2,305 deaths during treatment for a crude mortality rate of 1,021 deaths per 10,000 person-years. Traffic volumes and traffic densities in all buffers around patient residences were associated with increased mortality during TB treatment, although the findings were not statistically significant in all buffers. As the buffer size decreased, fifth-quintile mortality hazards increased, and trends across quintiles of traffic exposure became more statistically significant. Increasing quintiles of nearest-road traffic volumes in the 100-m buffer were associated with 3%, 14%, 19%, and 28% increased risk of death during TB treatment [first quintile, referent; second quintile hazard ratio (HR)=1.03 [95% confidence interval (CI): 0.86, 1.25]; third quintile HR=1.14 (95% CI: 0.95, 1.37); fourth quintile HR=1.19 (95% CI: 0.99, 1.43); fifth quintile HR=1.28 (95% CI: 1.07, 1.53), respectively; p-trend=0.002].

CONCLUSIONS

Residential proximity to road traffic volumes and traffic density were associated with increased all-cause mortality in patients undergoing treatment for active tuberculosis even after adjusting for multiple demographic, socioeconomic, and clinical factors, suggesting that TB patients are susceptible to the adverse health effects of traffic-related air pollution. https://doi.org/10.1289/EHP1699.

Factors Associated with Frailty and Its Trajectory among Patients on Hemodialysis

BACKGROUND AND OBJECTIVES

Frailty is common among patients on hemodialysis and associated with adverse outcomes. However, little is known about changes in frailty over time and the factors associated with those changes.

DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS

To address these questions, we examined 762 participants in the A Cohort to Investigate the Value of Exercise/Analyses Designed to Investigate the Paradox of Obesity and Survival in ESRD cohort study, among whom frailty was assessed at baseline and 12 and 24 months. We used ordinal generalized estimating equations analyses and modeled frailty (on a scale from zero to five possible components) and death during follow-up.

RESULTS

The mean frailty score at baseline was 1.9, and the distribution of frailty scores was similar at each evaluation. However, most participants' scores changed, with patients improving almost as often as worsening (overall change, 0.2 points per year; 95% confidence interval, 0.1 to 0.3). Hispanic ethnicity (0.6 points per year; 95% confidence interval, 0.0 to 1.1) and diabetes (0.7 points per year; 95% confidence interval, 0.3 to 1.0) were associated with higher frailty scores and higher serum albumin concentration with lower frailty scores (-1.1 points per g/dl; 95% confidence interval, -1.5 to -0.7). In addition, patients whose serum albumin increased over time were less likely to become frail, with each 1-g/dl increase in albumin associated with a 0.4-point reduction in frailty score (95% confidence interval, -0.80 to -0.05). To examine the underpinnings of the association between serum albumin and frailty, we included serum IL-6, normalized protein catabolic rate, and patient self-report of hospitalization within the last year in a second model. Higher IL-6 and hospitalization were statistically significantly associated with worse frailty at any point and worsening frailty over time, whereas normalized protein catabolic rate was not independently associated with frailty.

CONCLUSIONS

There was substantial year to year variability in frailty scores, with approximately equal numbers of patients improving and worsening. Markers of inflammation and hospitalization were independently associated with worsening frailty. Studies should examine whether interventions to address inflammation or posthospitalization rehabilitation can improve the trajectory of frailty.

Antiinflammatory Effects of Budesonide in Human Fetal Lung

Lung inflammation in premature infants contributes to the development of bronchopulmonary dysplasia (BPD), a chronic lung disease with long-term sequelae. Pilot studies administering budesonide suspended in surfactant have found reduced BPD without the apparent adverse effects that occur with systemic dexamethasone therapy. Our objective was to determine budesonide potency, stability, and antiinflammatory effects in human fetal lung. We cultured explants of second-trimester fetal lung with budesonide or dexamethasone and used microscopy, immunoassays, RNA sequencing, liquid chromatography/tandem mass spectrometry, and pulsating bubble surfactometry. Budesonide suppressed secreted chemokines IL-8 and CCL2 (MCP-1) within 4 hours, reaching a 90% decrease at 12 hours, which was fully reversed 72 hours after removal of the steroid. Half-maximal effects occurred at 0.04-0.05 nM, representing a fivefold greater potency than for dexamethasone. Budesonide significantly induced 3.6% and repressed 2.8% of 14,500 sequenced mRNAs by 1.6- to 95-fold, including 119 genes that contribute to the glucocorticoid inflammatory transcriptome; some are known targets of nuclear factor-κB. By global proteomics, 22 secreted inflammatory proteins were hormonally regulated. Two glucocorticoid-regulated genes of interest because of their association with lung disease are CHI3L1 and IL1RL1. Budesonide retained activity in the presence of surfactant and did not alter its surface properties. There was some formation of palmitate-budesonide in lung tissue but no detectable metabolism to inactive 16α-hydroxy prednisolone. We concluded that budesonide is a potent and stable antiinflammatory glucocorticoid in human fetal lung in vitro, supporting a beneficial antiinflammatory response to lung-targeted budesonide:surfactant treatment of infants for the prevention of BPD.

Immune Response and Mortality Risk Relate to Distinct Lung Microbiomes in Patients with HIV and Pneumonia

RATIONALE

The potential role of the airway microbiota in dictating immune responses and infection outcomes in HIV-associated pneumonia is largely unknown.

OBJECTIVES

To investigate whether microbiologically and immunologically distinct subsets of patients with HIV and pneumonia exist and are related to mortality.

METHODS

Bronchoalveolar lavage samples from Ugandan patients with HIV and pneumonia (n = 182) were obtained at study enrollment (following antibiotic treatment); patient demographics including 8- and 70-day mortality were collected. Lower airway bacterial community composition was assessed via amplification and sequencing of the V4 region of the 16S ribosomal RNA gene. Host immune response gene expression profiles were generated by quantitative polymerase chain reaction using RNA extracted from bronchoalveolar lavage fluid. Liquid and gas chromatography mass spectrometry was used to profile serum metabolites.

MEASUREMENTS AND MAIN RESULTS

Based on airway microbiome composition, most patients segregated into three distinct groups, each of which were predicted to encode metagenomes capable of producing metabolites characteristically enriched in paired serum samples from these patients. These three groups also exhibited differences in mortality; those with the highest rate had increased ceftriaxone administration and culturable Aspergillus, and demonstrated significantly increased induction of airway T-helper cell type 2 responses. The group with the lowest mortality was characterized by increased expression of T-cell immunoglobulin and mucin domain 3, which down-regulates T-helper cell type 1 proinflammatory responses and is associated with chronic viral infection.

CONCLUSIONS

These data provide evidence that compositionally and structurally distinct lower airway microbiomes are associated with discrete local host immune responses, peripheral metabolic reprogramming, and different rates of mortality.

Development and Validation of a Protein-Based Risk Score for Cardiovascular Outcomes Among Patients With Stable Coronary Heart Disease

IMPORTANCE

Precise stratification of cardiovascular risk in patients with coronary heart disease (CHD) is needed to inform treatment decisions.

OBJECTIVE

To derive and validate a score to predict risk of cardiovascular outcomes among patients with CHD, using large-scale analysis of circulating proteins.

DESIGN, SETTING, AND PARTICIPANTS

Prospective cohort study of participants with stable CHD. For the derivation cohort (Heart and Soul study), outpatients from San Francisco were enrolled from 2000 through 2002 and followed up through November 2011 (≤11.1 years). For the validation cohort (HUNT3, a Norwegian population-based study), participants were enrolled from 2006 through 2008 and followed up through April 2012 (5.6 years).

EXPOSURES

Using modified aptamers, 1130 proteins were measured in plasma samples.

MAIN OUTCOMES AND MEASURES

A 9-protein risk score was derived and validated for 4-year probability of myocardial infarction, stroke, heart failure, and all-cause death. Tests, including the C statistic, were used to assess performance of the 9-protein risk score, which was compared with the Framingham secondary event model, refit to the cohorts in this study. Within-person change in the 9-protein risk score was evaluated in the Heart and Soul study from paired samples collected 4.8 years apart.

RESULTS

From the derivation cohort, 938 samples were analyzed, participants' median age at enrollment was 67.0 years, and 82% were men. From the validation cohort, 971 samples were analyzed, participants' median age at enrollment was 70.2 years, and 72% were men. In the derivation cohort, C statistics were 0.66 for refit Framingham, 0.74 for 9-protein, and 0.75 for refit Framingham plus 9-protein models. In the validation cohort, C statistics were 0.64 for refit Framingham, 0.70 for 9-protein, and 0.71 for refit Framingham plus 9-protein models. Adding the 9-protein risk score to the refit Framingham model increased the C statistic by 0.09 (95% CI, 0.06-0.12) in the derivation cohort, and in the validation cohort, the C statistic was increased by 0.05 (95% CI, 0.02-0.09). Compared with the refit Framingham model, the integrated discrimination index for the 9-protein model was 0.12 (95% CI, 0.08-0.16) in the derivation cohort and 0.08 (95% CI, 0.05-0.10) in the validation cohort. In analysis of paired samples among 139 participants with cardiovascular events after the second sample, absolute within-person annualized risk increased more for the 9-protein model (median, 1.86% [95% CI, 1.15%-2.54%]) than for the refit Framingham model (median, 1.00% [95% CI, 0.87%-1.19%]) (P = .002), while among 375 participants without cardiovascular events, both scores changed less and similarly (P = .30).

CONCLUSIONS AND RELEVANCE

Among patients with stable CHD, a risk score based on 9 proteins performed better than the refit Framingham secondary event risk score in predicting cardiovascular events, but still provided only modest discriminative accuracy. Further research is needed to assess whether the score is more accurate in a lower-risk population.

Discovering hotspots in functional genomic data superposed on 3D chromatin configuration reconstructions

The spatial organization of the genome influences cellular function, notably gene regulation. Recent studies have assessed the three-dimensional (3D) co-localization of functional annotations (e.g. centromeres, long terminal repeats) using 3D genome reconstructions from Hi-C (genome-wide chromosome conformation capture) data; however, corresponding assessments for continuous functional genomic data (e.g. chromatin immunoprecipitation-sequencing (ChIP-seq) peak height) are lacking. Here, we demonstrate that applying bump hunting via the patient rule induction method (PRIM) to ChIP-seq data superposed on a Saccharomyces cerevisiae 3D genome reconstruction can discover ‘functional 3D hotspots’, regions in 3-space for which the mean ChIP-seq peak height is significantly elevated. For the transcription factor Swi6, the top hotspot by P-value contains MSB2 and ERG11 – known Swi6 target genes on different chromosomes. We verify this finding in a number of ways. First, this top hotspot is relatively stable under PRIM across parameter settings. Second, this hotspot is among the top hotspots by mean outcome identified by an alternative algorithm, k-Nearest Neighbor (k-NN) regression. Third, the distance between MSB2 and ERG11 is smaller than expected (by resampling) in two other 3D reconstructions generated via different normalization and reconstruction algorithms. This analytic approach can discover functional 3D hotspots and potentially reveal novel regulatory interactions.

Identification of Discrete Prognostic Groups in Ewing Sarcoma

BACKGROUND

Although multiple prognostic variables have been proposed for Ewing sarcoma (EWS), little work has been done to further categorize these variables into prognostic groups for risk classification.

PROCEDURE

We derived initial prognostic groups from 2,124 patients with EWS in the SEER database. We constructed a multivariable recursive partitioning model of overall survival using the following covariates: age; stage; race/ethnicity; sex; axial primary; pelvic primary; and bone or soft tissue primary. Based on this model, we identified risk groups and estimated 5-year overall survival for each group using Kaplan-Meier methods. We then applied these groups to 1,680 patients enrolled on COG clinical trials.

RESULTS

A multivariable model identified five prognostic groups with significantly different overall survival: (i) localized, age <18 years, non-pelvic primary; (ii) localized, age <18, pelvic primary or localized, age ≥18, white, non-Hispanic; (iii) localized, age ≥18, all races/ethnicities other than white, non-Hispanic; (iv) metastatic, age <18; and (v) metastatic, age ≥18. These five groups were applied to the COG dataset and showed significantly different overall and event-free survival based upon this classification system (P < 0.0001). A sub-analysis of COG patients treated with ifosfamide and etoposide as a component of therapy evaluated these findings in patients receiving contemporary therapy.

CONCLUSIONS

Recursive partitioning analysis yields discrete prognostic groups in EWS that provide valuable information for patients and clinicians in determining an individual patient's risk of death. These groups may enable future clinical trials to adjust EWS treatment according to individualized risk.

Reconstruction of 3D genome architecture via a two-stage algorithm

Background

The three-dimensional (3D) configuration of chromosomes within the eukaryote nucleus is an important factor for several cellular functions, including gene expression regulation, and has also been linked with cancer-causing translocation events. While visualization of such architecture remains limited to low resolutions, the ability to infer structures at increasing resolutions has been enabled by recently-devised chromosome conformation capture techniques. In particular, when coupled with next generation sequencing, such methods yield an inventory of genome-wide chromatin contacts or interactions. Various algorithms have been advanced to operate on such contact data to produce reconstructed 3D configurations. Studies have shown that these reconstructions can provide added value over raw interaction data with respect to downstream biological insights. However, only limited, low-resolution reconstructions have been realized for mammals due to computational bottlenecks.

Results

Here we propose a two-stage algorithm to partially overcome these computational barriers. The central idea is to initially utilize existing reconstruction techniques on an individual chromosome basis, using intra-chromosomal contacts, and then to relatively position these chromosome-level reconstructions using inter-chromosomal contacts. This two-stage strategy represents a natural approach in view of the within- versus between- chromosome distribution of contacts. It can increase resolution ≈ 20 fold for mouse and human. After describing the algorithm we present 3D architectures for mouse embryonic stem cells and human lymphoblastoid cells. We evaluate the impact of several factors on reconstruction reproducibility and explore a variety of sampling schemes. We further analyze replicate data at differing resolutions obtained from recently devised in situ Hi-C assays. In all instances we demonstrate insensitivity of the whole-genome 3D reconstruction obtained by the two-stage algorithm to the sampling strategy used.

Conclusions

Our two-stage algorithm has the potential to significantly increase the resolution of 3D genome reconstructions. The improvements are such that we can progress from 1 Mb resolution to 100 kb resolution, notable since this latter value has been identified as critical to inferring topological domains in analyses performed on the contact (rather than 3D) level.

Current theoretical models fail to predict the topological complexity of the human genome

Understanding the folding of the human genome is a key challenge of modern structural biology. The emergence of chromatin conformation capture assays (e.g., Hi-C) has revolutionized chromosome biology and provided new insights into the three dimensional structure of the genome. The experimental data are highly complex and need to be analyzed with quantitative tools. It has been argued that the data obtained from Hi-C assays are consistent with a fractal organization of the genome. A key characteristic of the fractal globule is the lack of topological complexity (knotting or inter-linking). However, the absence of topological complexity contradicts results from polymer physics showing that the entanglement of long linear polymers in a confined volume increases rapidly with the length and with decreasing volume. In vivo and in vitro assays support this claim in some biological systems. We simulate knotted lattice polygons confined inside a sphere and demonstrate that their contact frequencies agree with the human Hi-C data. We conclude that the topological complexity of the human genome cannot be inferred from current Hi-C data.

Distance-based assessment of the localization of functional annotations in 3D genome reconstructions

Background

Recent studies used the contact data or three-dimensional (3D) genome reconstructions from Hi-C (chromosome conformation capture with next-generation sequencing) to assess the co-localization of functional genomic annotations in the nucleus. These analyses dichotomized data point pairs belonging to a functional annotation as “close” or “far” based on some threshold and then tested for enrichment of “close” pairs. We propose an alternative approach that avoids dichotomization of the data and instead directly estimates the significance of distances within the 3D reconstruction.

Results

We applied this approach to 3D genome reconstructions for Plasmodium falciparum, the causative agent of malaria, and Saccharomyces cerevisiae and compared the results to previous approaches. We found significant 3D co-localization of centromeres, telomeres, virulence genes, and several sets of genes with developmentally regulated expression in P. falciparum; and significant 3D co-localization of centromeres and long terminal repeats in S. cerevisiae. Additionally, we tested the experimental observation that telomeres form three to seven clusters in P. falciparum and S. cerevisiae. Applying affinity propagation clustering to telomere coordinates in the 3D reconstructions yielded six telomere clusters for both organisms.

Conclusions

Distance-based assessment replicated key findings, while avoiding dichotomization of the data (which previously yielded threshold-sensitive results).

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-992) contains supplementary material, which is available to authorized users.

Development of a database for translational spinal cord injury research

Efforts to understand spinal cord injury (SCI) and other complex neurotrauma disorders at the pre-clinical level have shown progress in recent years. However, successful translation of basic research into clinical practice has been slow, partly because of the large, heterogeneous data sets involved. In this sense, translational neurological research represents a "big data" problem. In an effort to expedite translation of pre-clinical knowledge into standards of patient care for SCI, we describe the development of a novel database for translational neurotrauma research known as Visualized Syndromic Information and Outcomes for Neurotrauma-SCI (VISION-SCI). We present demographics, descriptive statistics, and translational syndromic outcomes derived from our ongoing efforts to build a multi-center, multi-species pre-clinical database for SCI models. We leveraged archived surgical records, postoperative care logs, behavioral outcome measures, and histopathology from approximately 3000 mice, rats, and monkeys from pre-clinical SCI studies published between 1993 and 2013. The majority of animals in the database have measures collected for health monitoring, such as weight loss/gain, heart rate, blood pressure, postoperative monitoring of bladder function and drug/fluid administration, behavioral outcome measures of locomotion, and tissue sparing postmortem. Attempts to align these variables with currently accepted common data elements highlighted the need for more translational outcomes to be identified as clinical endpoints for therapeutic testing. Last, we use syndromic analysis to identify conserved biological mechanisms of recovery after cervical SCI between rats and monkeys that will allow for more-efficient testing of therapeutics that will need to be translated toward future clinical trials.

Reproducibility of 3D chromatin configuration reconstructions

It is widely recognized that the three-dimensional (3D) architecture of eukaryotic chromatin plays an important role in processes such as gene regulation and cancer-driving gene fusions. Observing or inferring this 3D structure at even modest resolutions had been problematic, since genomes are highly condensed and traditional assays are coarse. However, recently devised high-throughput molecular techniques have changed this situation. Notably, the development of a suite of chromatin conformation capture (CCC) assays has enabled elicitation of contacts-spatially close chromosomal loci-which have provided insights into chromatin architecture. Most analysis of CCC data has focused on the contact level, with less effort directed toward obtaining 3D reconstructions and evaluating the accuracy and reproducibility thereof. While questions of accuracy must be addressed experimentally, questions of reproducibility can be addressed statistically-the purpose of this paper. We use a constrained optimization technique to reconstruct chromatin configurations for a number of closely related yeast datasets and assess reproducibility using four metrics that measure the distance between 3D configurations. The first of these, Procrustes fitting, measures configuration closeness after applying reflection, rotation, translation, and scaling-based alignment of the structures. The others base comparisons on the within-configuration inter-point distance matrix. Inferential results for these metrics rely on suitable permutation approaches. Results indicate that distance matrix-based approaches are preferable to Procrustes analysis, not because of the metrics per se but rather on account of the ability to customize permutation schemes to handle within-chromosome contiguity. It has recently been emphasized that the use of constrained optimization approaches to 3D architecture reconstruction are prone to being trapped in local minima. Our methods of reproducibility assessment provide a means for comparing 3D reconstruction solutions so that we can discern between local and global optima by contrasting solutions under perturbed inputs.

Monocyte activation by interferon α is associated with failure to achieve a sustained virologic response after treatment for hepatitis C virus infection

BACKGROUND

Interferon α (IFN-α) and ribavirin can induce a sustained virologic response (SVR) in some but not all hepatitis C virus (HCV)-infected patients. The mechanism of effective treatment is unclear. One possibility is that IFN-α differentially improves the functional capacity of classic myeloid dendritic cells (mDCs) by altering expression of surface molecules or cytokines. Others have proposed that antigen-presenting cell activation could be paradoxically detrimental during HCV infection because of the production by monocytes of substances inhibitory or toxic to plasmacytoid dendritic cells.

METHODS

We examined responses to in vitro IFN-α treatment of peripheral blood leukocyte samples from a retrospective treatment cohort of nearly 200 HCV-seropositive patients who had undergone antiviral therapy with ribavirin and pegylated IFN. We analyzed the variable responses of antigen-presenting cell subsets to drug.

RESULTS

We found that patients achieving SVR were no more likely to have robust mDC activation in response to IFN-α than those who did not achieve SVR. Rather, patients achieving SVR were distinguished by restrained monocyte activation in the presence of IFN-α, a factor that was second in importance only to IL28B genotype in its association with SVR.

CONCLUSIONS

These results suggest that interindividual variability in the response of monocytes to IFN-α is an important determinant of treatment success with IFN-α-based regimens.

Derivation of multivariate syndromic outcome metrics for consistent testing across multiple models of cervical spinal cord injury in rats

Spinal cord injury (SCI) and other neurological disorders involve complex biological and functional changes. Well-characterized preclinical models provide a powerful tool for understanding mechanisms of disease; however managing information produced by experimental models represents a significant challenge for translating findings across research projects and presents a substantial hurdle for translation of novel therapies to humans. In the present work we demonstrate a novel ‘syndromic’ information-processing approach for capitalizing on heterogeneous data from diverse preclinical models of SCI to discover translational outcomes for therapeutic testing. We first built a large, detailed repository of preclinical outcome data from 10 years of basic research on cervical SCI in rats, and then applied multivariate pattern detection techniques to extract features that are conserved across different injury models. We then applied this translational knowledge to derive a data-driven multivariate metric that provides a common ‘ruler’ for comparisons of outcomes across different types of injury (NYU/MASCIS weight drop injuries, Infinite Horizons (IH) injuries, and hemisection injuries). The findings revealed that each individual endpoint provides a different view of the SCI syndrome, and that considering any single outcome measure in isolation provides a misleading, incomplete view of the SCI syndrome. This limitation was overcome by taking a novel multivariate integrative approach for leveraging complex data from preclinical models of neurological disease to identify therapies that target multiple outcomes. We suggest that applying this syndromic approach provides a roadmap for translating therapies for SCI and other complex neurological diseases.

A histone arginine methylation localizes to nucleosomes in satellite II and III DNA sequences in the human genome

Background

Applying supervised learning/classification techniques to epigenomic data may reveal properties that differentiate histone modifications. Previous analyses sought to classify nucleosomes containing histone H2A/H4 arginine 3 symmetric dimethylation (H2A/H4R3me2s) or H2A.Z using human CD4⁺ T-cell chromatin immunoprecipitation sequencing (ChIP-Seq) data. However, these efforts only achieved modest accuracy with limited biological interpretation. Here, we investigate the impact of using appropriate data pre-processing —deduplication, normalization, and position- (peak-) finding to identify stable nucleosome positions — in conjunction with advanced classification algorithms, notably discriminatory motif feature selection and random forests. Performance assessments are based on accuracy and interpretative yield.

Results

We achieved dramatically improved accuracy using histone modification features (99.0%; previous attempts, 68.3%) and DNA sequence features (94.1%; previous attempts, <60%). Furthermore, the algorithms elicited interpretable features that withstand permutation testing, including: the histone modifications H4K20me3 and H3K9me3, which are components of heterochromatin; and the motif TCCATT, which is part of the consensus sequence of satellite II and III DNA. Downstream analysis demonstrates that satellite II and III DNA in the human genome is occupied by stable nucleosomes containing H2A/H4R3me2s, H4K20me3, and/or H3K9me3, but not 18 other histone methylations. These results are consistent with the recent biochemical finding that H4R3me2s provides a binding site for the DNA methyltransferase (Dnmt3a) that methylates satellite II and III DNA.

Conclusions

Classification algorithms applied to appropriately pre-processed ChIP-Seq data can accurately discriminate between histone modifications. Algorithms that facilitate interpretation, such as discriminatory motif feature selection, have the added potential to impart information about underlying biological mechanism.

A practical molecular assay to predict survival in resected non-squamous, non-small-cell lung cancer: development and international validation studies

BACKGROUND

The frequent recurrence of early-stage non-small-cell lung cancer (NSCLC) is generally attributable to metastatic disease undetected at complete resection. Management of such patients depends on prognostic staging to identify the individuals most likely to have occult disease. We aimed to develop and validate a practical, reliable assay that improves risk stratification compared with conventional staging.

METHODS

A 14-gene expression assay that uses quantitative PCR, runs on formalin-fixed paraffin-embedded tissue samples, and differentiates patients with heterogeneous statistical prognoses was developed in a cohort of 361 patients with non-squamous NSCLC resected at the University of California, San Francisco. The assay was then independently validated by the Kaiser Permanente Division of Research in a masked cohort of 433 patients with stage I non-squamous NSCLC resected at Kaiser Permanente Northern California hospitals, and on a cohort of 1006 patients with stage I-III non-squamous NSCLC resected in several leading Chinese cancer centres that are part of the China Clinical Trials Consortium (CCTC).

FINDINGS

Kaplan-Meier analysis of the Kaiser validation cohort showed 5 year overall survival of 71·4% (95% CI 60·5-80·0) in low-risk, 58·3% (48·9-66·6) in intermediate-risk, and 49·2% (42·2-55·8) in high-risk patients (p(trend)=0·0003). Similar analysis of the CCTC cohort indicated 5 year overall survivals of 74·1% (66·0-80·6) in low-risk, 57·4% (48·3-65·5) in intermediate-risk, and 44·6% (40·2-48·9) in high-risk patients (p(trend)<0·0001). Multivariate analysis in both cohorts indicated that no standard clinical risk factors could account for, or provide, the prognostic information derived from tumour gene expression. The assay improved prognostic accuracy beyond National Comprehensive Cancer Network criteria for stage I high-risk tumours (p<0·0001), and differentiated low-risk, intermediate-risk, and high-risk patients within all disease stages.

INTERPRETATION

Our practical, quantitative-PCR-based assay reliably identified patients with early-stage non-squamous NSCLC at high risk for mortality after surgical resection.

FUNDING

UCSF Thoracic Oncology Laboratory and Pinpoint Genomics.

Functional hot spots in human ATP-binding cassette transporter nucleotide binding domains

The human ATP-binding cassette (ABC) transporter superfamily consists of 48 integral membrane proteins that couple the action of ATP binding and hydrolysis to the transport of diverse substrates across cellular membranes. Defects in 18 transporters have been implicated in human disease. In hundreds of cases, disease phenotypes and defects in function can be traced to nonsynonymous single nucleotide polymorphisms (nsSNPs). The functional impact of the majority of ABC transporter nsSNPs has yet to be experimentally characterized. Here, we combine experimental mutational studies with sequence and structural analysis to describe the impact of nsSNPs in human ABC transporters. First, the disease associations of 39 nsSNPs in 10 transporters were rationalized by identifying two conserved loops and a small α-helical region that may be involved in interdomain communication necessary for transport of substrates. Second, an approach to discriminate between disease-associated and neutral nsSNPs was developed and tailored to this superfamily. Finally, the functional impact of 40 unannotated nsSNPs in seven ABC transporters identified in 247 ethnically diverse individuals studied by the Pharmacogenetics of Membrane Transporters consortium was predicted. Three predictions were experimentally tested using human embryonic kidney epithelial (HEK) 293 cells stably transfected with the reference multidrug resistance transporter 4 and its variants to examine functional differences in transport of the antiviral drug, tenofovir. The experimental results confirmed two predictions. Our analysis provides a structural and evolutionary framework for rationalizing and predicting the functional effects of nsSNPs in this clinically important membrane transporter superfamily.

Clustering with exclusion zones: genomic applications

Methods for formally evaluating the clustering of events in space or time, notably the scan statistic, have been richly developed and widely applied. In order to utilize the scan statistic and related approaches, it is necessary to know the extent of the spatial or temporal domains wherein the events arise. Implicit in their usage is that these domains have no "holes"-hereafter "exclusion zones"-regions in which events a priori cannot occur. However, in many contexts, this requirement is not met. When the exclusion zones are known, it is straightforward to correct the scan statistic for their occurrence by simply adjusting the extent of the domain. Here, we tackle the more ambitious objective of formally evaluating clustering in the presence of "unknown" exclusion zones. We develop an algorithm for estimating total exclusion zone extent, the quantity needed to correct scan statistic-based inference, using distributional properties of "spacings," and show how bias correction for this estimator can be effected. Performance of the algorithm is assessed via simulation study. We showcase applications to genomic settings for differing marker (event) types-binding sites, housekeeping genes, and microRNAs-wherein exclusion zones can arise through a variety of mechanisms. In several instances, dramatic changes to unadjusted inference that does not accommodate exclusions are evidenced.

Regulated gene expression in cultured type II cells of adult human lung

Alveolar type II cells have multiple functions, including surfactant production and fluid clearance, which are critical for lung function. Differentiation of type II cells occurs in cultured fetal lung epithelial cells treated with dexamethasone plus cAMP and isobutylmethylxanthine (DCI) and involves increased expression of 388 genes. In this study, type II cells of human adult lung were isolated at approximately 95% purity, and gene expression was determined (Affymetrix) before and after culturing 5 days on collagen-coated dishes with or without DCI for the final 3 days. In freshly isolated cells, highly expressed genes included SFTPA/B/C, SCGB1A, IL8, CXCL2, and SFN in addition to ubiquitously expressed genes. Transcript abundance was correlated between fetal and adult cells (r = 0.88), with a subset of 187 genes primarily related to inflammation and immunity that were expressed >10-fold higher in adult cells. During control culture, expression increased for 8.1% of expressed genes and decreased for approximately 4% including 118 immune response and 10 surfactant-related genes. DCI treatment promoted lamellar body production and increased expression of approximately 3% of probed genes by > or =1.5-fold; 40% of these were also induced in fetal cells. Highly induced genes (> or =10-fold) included PGC, ZBTB16, DUOX1, PLUNC, CIT, and CRTAC1. Twenty-five induced genes, including six genes related to surfactant (SFTPA/B/C, PGC, CEBPD, and ADFP), also had decreased expression during control culture and thus are candidates for hormonal regulation in vivo. Our results further define the adult human type II cell molecular phenotype and demonstrate that a subset of genes remains hormone responsive in cultured adult cells.

Lactobacillus casei abundance is associated with profound shifts in the infant gut microbiome

Colonization of the infant gut by microorganisms over the first year of life is crucial for development of a balanced immune response. Early alterations in the gastrointestinal microbiota of neonates has been linked with subsequent development of asthma and atopy in older children. Here we describe high-resolution culture-independent analysis of stool samples from 6-month old infants fed daily supplements of Lactobacillus casei subsp. Rhamnosus (LGG) or placebo in a double-blind, randomized Trial of Infant Probiotic Supplementation (TIPS). Bacterial community composition was examined using a high-density microarray, the 16S rRNA PhyloChip, and the microbial assemblages of infants with either high or low LGG abundance were compared. Communities with high abundance of LGG exhibited promotion of phylogenetically clustered taxa including a number of other known probiotic species, and were significantly more even in their distribution of community members. Ecologically, these aspects are characteristic of communities that are more resistant to perturbation and outgrowth of pathogens. PhyloChip analysis also permitted identification of taxa negatively correlated with LGG abundance that have previously been associated with atopy, as well as those positively correlated that may prove useful alternative targets for investigation as alternative probiotic species. From these findings we hypothesize that a key mechanism for the protective effect of LGG supplementation on subsequent development of allergic disease is through promotion of a stable, even, and functionally redundant infant gastrointestinal community.

Differentiation of recurrent glioblastoma multiforme from radiation necrosis after external beam radiation therapy with dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging

PURPOSE

To investigate whether cerebral blood volume (CBV), peak height (PH), and percentage of signal intensity recovery (PSR) measurements derived from the results of T2-weighted dynamic susceptibility-weighted contrast material-enhanced (DSC) magnetic resonance (MR) imaging performed after external beam radiation therapy (EBRT) can be used to distinguish recurrent glioblastoma multiforme (GBM) from radiation necrosis.

MATERIALS AND METHODS

Fifty-seven patients were enrolled in this HIPAA-compliant institutional review board-approved retrospective study after they received a diagnosis of GBM, underwent EBRT, and were examined with DSC MR imaging, which revealed progressive contrast enhancement within the radiation field. A definitive diagnosis was established at subsequent surgical resection or clinicoradiologic follow-up. Regions of interest were retrospectively drawn around the entire contrast-enhanced region. This created T2-weighted signal intensity-time curves that produced three cerebral hemodynamic MR imaging measurements: CBV, PH, and PSR. Welch t tests were used to compare measurements between groups.

RESULTS

Mean, maximum, and minimum relative PH and relative CBV were significantly higher (P < .01) in patients with recurrent GBM than in patients with radiation necrosis. Mean, maximum, and minimum relative PSR values were significantly lower (P < .05) in patients with recurrent GBM than in patients with radiation necrosis.

CONCLUSION

These findings suggest that DSC perfusion MR imaging may be used to differentiate recurrent GBM from EBRT-induced radiation necrosis.

A novel topology for representing protein folds

Various topologies for representing 3D protein structures have been advanced for purposes ranging from prediction of folding rates to ab initio structure prediction. Examples include relative contact order, Delaunay tessellations, and backbone torsion angle distributions. Here, we introduce a new topology based on a novel means for operationalizing 3D proximities with respect to the underlying chain. The measure involves first interpreting a rank-based representation of the nearest neighbors of each residue as a permutation, then determining how perturbed this permutation is relative to an unfolded chain. We show that the resultant topology provides improved association with folding and unfolding rates determined for a set of two-state proteins under standardized conditions. Furthermore, unlike existing topologies, the proposed geometry exhibits fine scale structure with respect to sequence position along the chain, potentially providing insights into folding initiation and/or nucleation sites.

Identification of yeast transcriptional regulation networks using multivariate random forests

The recent availability of whole-genome scale data sets that investigate complementary and diverse aspects of transcriptional regulation has spawned an increased need for new and effective computational approaches to analyze and integrate these large scale assays. Here, we propose a novel algorithm, based on random forest methodology, to relate gene expression (as derived from expression microarrays) to sequence features residing in gene promoters (as derived from DNA motif data) and transcription factor binding to gene promoters (as derived from tiling microarrays). We extend the random forest approach to model a multivariate response as represented, for example, by time-course gene expression measures. An analysis of the multivariate random forest output reveals complex regulatory networks, which consist of cohesive, condition-dependent regulatory cliques. Each regulatory clique features homogeneous gene expression profiles and common motifs or synergistic motif groups. We apply our method to several yeast physiological processes: cell cycle, sporulation, and various stress conditions. Our technique displays excellent performance with regard to identifying known regulatory motifs, including high order interactions. In addition, we present evidence of the existence of an alternative MCB-binding pathway, which we confirm using data from two independent cell cycle studies and two other physioloigical processes. Finally, we have uncovered elaborate transcription regulation refinement mechanisms involving PAC and mRRPE motifs that govern essential rRNA processing. These include intriguing instances of differing motif dosages and differing combinatorial motif control that promote regulatory specificity in rRNA metabolism under differing physiological processes.

Personalized prediction of tumor response and cancer progression on prostate needle biopsy

PURPOSE

To our knowledge in patients with prostate cancer there are no available tests except clinical variables to determine the likelihood of disease progression. We developed a patient specific, biology driven tool to predict outcome at diagnosis. We also investigated whether biopsy androgen receptor levels predict a durable response to therapy after secondary treatment.

MATERIALS AND METHODS

We evaluated paraffin embedded prostate needle biopsy tissue from 1,027 patients with cT1c-T3 prostate cancer treated with surgery and followed a median of 8 years. Machine learning was done to integrate clinical data with biopsy quantitative biometric features. Multivariate models were constructed to predict disease progression with the C index to estimate performance.

RESULTS

In a training set of 686 patients (total of 87 progression events) 3 clinical and 3 biopsy tissue characteristics were identified to predict clinical progression within 8 years after prostatectomy with 78% sensitivity, 69% specificity, a C index of 0.74 and a HR of 5.12. Validation in an independent cohort of 341 patients (total of 44 progression events) yielded 76% sensitivity, 64% specificity, a C index of 0.73 and a HR of 3.47. Increased androgen receptor in tumor cells in the biopsy highly significantly predicted resistance to therapy, ie androgen ablation with or without salvage radiotherapy, and clinical failure (p <0.0001).

CONCLUSIONS

Morphometry reliably classifies Gleason pattern 3 tumors. When combined with biomarker data, it adds to the hematoxylin and eosin analysis, and prostate specific antigen values currently used to assess outcome at diagnosis. Biopsy androgen receptor levels predict the likelihood of a response to therapy after recurrence and may guide future treatment decisions.

Distinguishing recurrent intra-axial metastatic tumor from radiation necrosis following gamma knife radiosurgery using dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging

BACKGROUND AND PURPOSE

MR image-guided gamma knife radiosurgery is often used to treat intra-axial metastatic neoplasms. Following treatment, it is often difficult to determine whether a progressively enhancing lesion is due to metastatic tumor recurrence or radiation necrosis. The purpose of our study was to determine whether relative cerebral blood volume (rCBV), relative peak height (rPH), and percentage of signal-intensity recovery (PSR) derived from dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging can distinguish recurrent metastatic tumor from radiation necrosis.

MATERIALS AND METHODS

Twenty-seven patients with systemic cancer underwent gamma knife radiosurgery for metastatic lesions of the brain and subsequently developed enlarging regions of enhancement within the radiation field. Subsequent surgical resection or clinicoradiologic follow-up established a diagnosis of recurrent metastatic tumor or radiation necrosis. Perfusion MR imaging datasets were retrospectively reprocessed, and regions of interest were drawn around the entire contrast-enhancing region. The resulting T2* signal-intensity time curves produced rCBV, rPH, and PSR values for each examination. A Welch t test was used to compare imaging values between groups.

RESULTS

The mean, minimum, and maximum PSR values were significantly lower (P < .01) in cases of recurrent metastatic tumor. The mean and maximum rCBV and rPH values were significantly higher (P < .02) in the recurrent metastatic tumor group.

CONCLUSIONS

The findings of our study suggest that perfusion MR imaging may be used to differentiate recurrent intra-axial metastatic tumor from gamma knife-induced radiation necrosis.

Simple, defensible sample sizes based on cost efficiency

The conventional approach of choosing sample size to provide 80% or greater power ignores the cost implications of different sample size choices. Costs, however, are often impossible for investigators and funders to ignore in actual practice. Here, we propose and justify a new approach for choosing sample size based on cost efficiency, the ratio of a study's projected scientific and/or practical value to its total cost. By showing that a study's projected value exhibits diminishing marginal returns as a function of increasing sample size for a wide variety of definitions of study value, we are able to develop two simple choices that can be defended as more cost efficient than any larger sample size. The first is to choose the sample size that minimizes the average cost per subject. The second is to choose sample size to minimize total cost divided by the square root of sample size. This latter method is theoretically more justifiable for innovative studies, but also performs reasonably well and has some justification in other cases. For example, if projected study value is assumed to be proportional to power at a specific alternative and total cost is a linear function of sample size, then this approach is guaranteed either to produce more than 90% power or to be more cost efficient than any sample size that does. These methods are easy to implement, based on reliable inputs, and well justified, so they should be regarded as acceptable alternatives to current conventional approaches.