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1.  Candidate Gene Association Study of Coronary Artery Calcification in Chronic Kidney Disease: Findings from the Chronic Renal Insufficiency Cohort Study 
Objectives
To identify loci for coronary artery calcification (CAC) in patients with chronic kidney disease (CKD).
Background
CKD is associated with increased CAC and subsequent coronary heart disease (CHD) but the mechanisms remain poorly defined. Genetic studies of CAC in CKD may provide a useful strategy for identifying novel pathways in CHD.
Methods
We performed a candidate gene study (~2,100 genes; ~50,000 SNPs) of CAC within the Chronic Renal Insufficiency Cohort (CRIC) Study (n=1,509; 57% European, 43% African ancestry). SNPs with preliminary evidence of association with CAC in CRIC were examined for association with CAC in PennCAC (n=2,560) and Amish Family Calcification Study (AFCS; n=784) samples. SNPs with suggestive replication were further analyzed for association with myocardial infarction (MI) in the Pakistan Risk of Myocardial Infarction study (PROMIS) (n=14,885).
Results
Of 268 SNPs reaching P <5×10−4 for CAC in CRIC, 28 SNPs in 23 loci had nominal support (P <0.05 and in same direction) for CAC in PennCAC or AFCS. Besides chr9p21 and COL4A1, known loci for CHD, these included SNPs having reported GWAS association with hypertension (e.g., ATP2B1). In PROMIS, four of the 23 suggestive CAC loci (chr9p21, COL4A1, ATP2B1 and ABCA4) had significant associations with MI consistent with their direction of effect on CAC.
Conclusions
We identified several loci associated with CAC in CKD that also relate to MI in a general population sample. CKD imparts a high risk of CHD and may provide a useful setting for discovery of novel CHD genes and pathways.
doi:10.1016/j.jacc.2013.01.103
PMCID: PMC3953823  PMID: 23727086
Coronary artery calcification (CAC); chronic kidney disease (CKD); Chronic Renal Insufficiency Cohort Study (CRIC); myocardial infarction (MI); risk factors; candidate genes; single nucleotide polymorphisms (SNPs)
2.  Pegylated Interferon Alfa-2a Monotherapy Results in Suppression of HIV Type 1 Replication and Decreased Cell-Associated HIV DNA Integration 
The Journal of Infectious Diseases  2012;207(2):213-222.
Background. Antiretroviral therapy (ART)–mediated immune reconstitution fails to restore the capacity of the immune system to spontaneously control human immunodeficiency virus (HIV) replication.
Methods. A total of 23 HIV type 1 (HIV-1)–infected, virologically suppressed subjects receiving ART (CD4+ T-cell count, >450 cells/μL) were randomly assigned to have 180 μg/week (for arm A) or 90 μg/week (for arm B) of pegylated (Peg) interferon alfa-2a added to their current ART regimen. After 5 weeks, ART was interrupted, and Peg–interferon alfa-2a was continued for up to 12 weeks (the primary end point), with an option to continue to 24 weeks. End points included virologic failure (viral load, ≥400 copies/mL) and adverse events. Residual viral load and HIV-1 DNA integration were also assessed.
Results. At week 12 of Peg–interferon alfa-2a monotherapy, viral suppression was observed in 9 of 20 subjects (45%), a significantly greater proportion than expected (arm A, P = .0088; arm B, P = .0010; combined arms, P < .0001). Over 24 weeks, both arms had lower proportions of subjects who had viral load, compared with the proportion of subjects in a historical control group (arm A, P = .0046; arm B, P = .0011). Subjects who had a sustained viral load of <400 copies/mL had decreased levels of integrated HIV DNA (P = .0313) but increased residual viral loads (P = .0078), compared with subjects who experienced end-point failure.
Conclusions. Peg–interferon alfa-2a immunotherapy resulted in control of HIV replication and decreased HIV-1 integration, supporting a role for immunomediated approaches in HIV suppression and/or eradication.
Clinical Trials Registration. NCT00594880.
doi:10.1093/infdis/jis663
PMCID: PMC3532820  PMID: 23105144
HIV-1; interferon-alpha; viral integration; immunotherapy
3.  Mixed Modeling of Meta-Analysis P-Values (MixMAP) Suggests Multiple Novel Gene Loci for Low Density Lipoprotein Cholesterol 
PLoS ONE  2013;8(2):e54812.
Informing missing heritability for complex disease will likely require leveraging information across multiple SNPs within a gene region simultaneously to characterize gene and locus-level contributions to disease phenotypes. To this aim, we introduce a novel strategy, termed Mixed modeling of Meta-Analysis P-values (MixMAP), that draws on a principled statistical modeling framework and the vast array of summary data now available from genetic association studies, to test formally for locus level association. The primary inputs to this approach are: (a) single SNP level p-values for tests of association; and (b) the mapping of SNPs to genomic regions. The output of MixMAP is comprised of locus level estimates and tests of association. In application of MixMAP to summary data from the Global Lipids Gene Consortium, we suggest twelve new loci (PKN, FN1, UGT1A1, PPARG, DMDGH, PPARD, CDK6, VPS13B, GAD2, GAB2, APOH and NPC1) for low-density lipoprotein cholesterol (LDL-C), a causal risk factor for cardiovascular disease and we also demonstrate the potential utility of MixMAP in small data settings. Overall, MixMAP offers novel and complementary information as compared to SNP-based analysis approaches and is straightforward to implement with existing open-source statistical software tools.
doi:10.1371/journal.pone.0054812
PMCID: PMC3566142  PMID: 23405096
4.  Increased Microbial Translocation in ≤180 Days Old Perinatally Human Immunodeficiency Virus Positive Infants as Compared with Human Immunodeficiency Virus -Exposed/Uninfected Infants of Similar Age 
Background
We investigated the effect of early versus deferred antiretroviral treatment (ART) on plasma concentration of lipopolysaccharide (LPS) and host LPS-binding molecules in HIV-infected infants up to 1 year of age.
Methods
We evaluated 54 perinatally HIV-infected and 22 HIV-exposed/uninfected infants (controls) at the first and second semester of life. All HIV-infected infants had a baseline CD4≥25%, participated in the CIPRA-SA Children with HIV Early Antiretroviral Therapy (CHER) trial in South Africa and were randomized in: Group 1 (n=20), ART deferred until CD4<25% or severe HIV disease, and Group 2 (n=34), ART initiation within 6-12 weeks of age. LPS, endotoxin-core antibodies (EndoCAb), soluble (s)CD14, and LPS-binding protein (LBP) were measured in cryopreserved plasma. T cell activation was measured in fresh whole blood.
Results
At the first semester, LPS concentration was higher in HIV-infected infants than in controls; sCD14, LBP and T cell activation were higher in Group 1 than in Group 2 and controls. While LPS was not correlated with study variables, viral load was positively associated with sCD14, LBP or EndoCAb. At the second semester, LPS was not detectable and elevated host LPS-control molecules values were sustained, in all groups and in conjunction with ART in all HIV-infected infants.
Conclusions
While plasma concentration of LPS is higher in perinatally HIV-infected infants 0-6 months of age than in controls independent of ART initiation strategy, LPS-control molecules concentration is higher in infants with deferred ART, suggesting the presence of increased microbial translocation in HIV-infected infants with sustained early viral replication.
doi:10.1097/INF.0b013e31821d141e
PMCID: PMC3173518  PMID: 21552185
HIV-1-infected infants; LPS; microbial translocation; LPS-binding molecules
5.  Ridge Regression for Longitudinal Biomarker Data 
Technological advances facilitating the acquisition of large arrays of biomarker data have led to new opportunities to understand and characterize disease progression over time. This creates an analytical challenge, however, due to the large numbers of potentially informative markers, the high degrees of correlation among them, and the time-dependent trajectories of association. We propose a mixed ridge estimator, which integrates ridge regression into the mixed effects modeling framework in order to account for both the correlation induced by repeatedly measuring an outcome on each individual over time, as well as the potentially high degree of correlation among possible predictor variables. An expectation-maximization algorithm is described to account for unknown variance and covariance parameters. Model performance is demonstrated through a simulation study and an application of the mixed ridge approach to data arising from a study of cardiometabolic biomarker responses to evoked inflammation induced by experimental low-dose endotoxemia.
doi:10.2202/1557-4679.1353
PMCID: PMC3202941  PMID: 22049265
biomarkers; cardiovascular disease (CVD); mixed effects; repeated measures; ridge regression
6.  Latent variable modeling paradigms for genotype-trait association studies 
Characterizing associations among multiple single-nucleotide polymorphisms (SNPs) within and across genes, and measures of disease progression or disease status will potentially offer new insight into disease etiology and disease progression. However, this presents a significant analytic challenge due to the existence of multiple potentially informative genetic loci, as well as environmental and demographic factors, and the generally uncharacterized and complex relationships among them. Latent variable modeling approaches offer a natural, yet underutilized, framework for analysis of data arising from these population-based genetic association investigations of complex diseases as they are well-suited to uncover simultaneous effects of multiple markers. In this manuscript we describe application and performance of two such latent variable methods, namely structural equation models (SEMs) and mixed effects models (MEMs), and highlight their theoretical overlap. The relative advantages of each paradigm is investigated through simulation studies and, finally, an application to data arising from a study of anti-retroviral associated dyslipidemia in HIV-infected individuals is provided for illustration.
doi:10.1002/bimj.201000218
PMCID: PMC3312474  PMID: 21887796
Mixed Effects Models; Single-nucleotide polymorphisms (SNPs); Structural equation model (SEM)
7.  Mixture modelling as an exploratory framework for genotype–trait associations 
Summary
We propose a mixture modelling framework for both identifying and exploring the nature of genotype–trait associations. This framework extends the classical mixed effects modelling approach for this setting by incorporating a Gaussian mixture distribution for random genotype effects. The primary advantages of this paradigm over existing approaches include that the mixture modelling framework addresses the degrees-of-freedom challenge that is inherent in application of the usual fixed effects analysis of covariance, relaxes the restrictive single normal distribution assumption of the classical mixed effects models and offers an exploratory framework for discovery of underlying structure across multiple genetic loci. An application to data arising from a study of antiretroviral-associated dyslipidaemia in human immunodeficiency virus infection is presented. Extensive simulations studies are also implemented to investigate the performance of this approach.
doi:10.1111/j.1467-9876.2010.00750.x
PMCID: PMC3285383  PMID: 22368304
Genetic associations; Latent class; Mixture models
8.  Prioritizing CD4 Count Monitoring in Response to ART in Resource-Constrained Settings: A Retrospective Application of Prediction-Based Classification 
PLoS Medicine  2012;9(4):e1001207.
Luis Montaner and colleagues retrospectively apply a potential capacity-saving CD4 count prediction tool to a cohort of HIV patients on antiretroviral therapy.
Background
Global programs of anti-HIV treatment depend on sustained laboratory capacity to assess treatment initiation thresholds and treatment response over time. Currently, there is no valid alternative to CD4 count testing for monitoring immunologic responses to treatment, but laboratory cost and capacity limit access to CD4 testing in resource-constrained settings. Thus, methods to prioritize patients for CD4 count testing could improve treatment monitoring by optimizing resource allocation.
Methods and Findings
Using a prospective cohort of HIV-infected patients (n = 1,956) monitored upon antiretroviral therapy initiation in seven clinical sites with distinct geographical and socio-economic settings, we retrospectively apply a novel prediction-based classification (PBC) modeling method. The model uses repeatedly measured biomarkers (white blood cell count and lymphocyte percent) to predict CD4+ T cell outcome through first-stage modeling and subsequent classification based on clinically relevant thresholds (CD4+ T cell count of 200 or 350 cells/µl). The algorithm correctly classified 90% (cross-validation estimate = 91.5%, standard deviation [SD] = 4.5%) of CD4 count measurements <200 cells/µl in the first year of follow-up; if laboratory testing is applied only to patients predicted to be below the 200-cells/µl threshold, we estimate a potential savings of 54.3% (SD = 4.2%) in CD4 testing capacity. A capacity savings of 34% (SD = 3.9%) is predicted using a CD4 threshold of 350 cells/µl. Similar results were obtained over the 3 y of follow-up available (n = 619). Limitations include a need for future economic healthcare outcome analysis, a need for assessment of extensibility beyond the 3-y observation time, and the need to assign a false positive threshold.
Conclusions
Our results support the use of PBC modeling as a triage point at the laboratory, lessening the need for laboratory-based CD4+ T cell count testing; implementation of this tool could help optimize the use of laboratory resources, directing CD4 testing towards higher-risk patients. However, further prospective studies and economic analyses are needed to demonstrate that the PBC model can be effectively applied in clinical settings.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
AIDS has killed nearly 30 million people since 1981, and about 34 million people (most of them living in low- and middle-income countries) are now infected with HIV, the virus that causes AIDS. HIV destroys immune system cells (including CD4 cells, a type of lymphocyte and one of the body's white blood cell types), leaving infected individuals susceptible to other infections. Early in the AIDS epidemic, most HIV-infected people died within ten years of infection. Then, in 1996, antiretroviral therapy (ART) became available, and for people living in affluent countries, HIV/AIDS became a chronic condition. However, ART was expensive, and for people living in developing countries, HIV/AIDS remained a fatal illness. In 2003, HIV was declared a global health emergency, and in 2006, the international community set itself the target of achieving universal access to ART by 2010. By the end of 2010, only 6.6 million of the estimated 15 million people in need of ART in developing countries were receiving ART.
Why Was This Study Done?
One factor that has impeded progress towards universal ART coverage has been the limited availability of trained personnel and laboratory facilities in many developing countries. These resources are needed to determine when individuals should start ART—the World Health Organization currently recommends that people start ART when their CD4 count drops below 350 cells/µl—and to monitor treatment responses over time so that viral resistance to ART is quickly detected. Although a total lymphocyte count can be used as a surrogate measure to decide when to start treatment, repeated CD4 cell counts are the only way to monitor immunologic responses to treatment, a level of monitoring that is rarely sustainable in resource-constrained settings. A method that optimizes resource allocation by prioritizing who gets tested might be one way to improve treatment monitoring. In this study, the researchers applied a new tool for prioritizing laboratory-based CD4 cell count testing in resource-constrained settings to patient data that had been previously collected.
What Did the Researchers Do and Find?
The researchers fitted a mixed-effects statistical model to repeated CD4 count measurements from HIV-infected individuals from seven sites around the world (including some resource-limited sites). They then used model-derived estimates to apply a mathematical tool for predicting—from a CD4 count taken at the start of treatment, and white blood cell counts and lymphocyte percentage measurements taken later—whether CD4 counts would be above 200 cells/µl (the original threshold recommended for ART initiation) and 350 cells/µl (the current recommended threshold) for up to three years after ART initiation. The tool correctly classified 91.5% of the CD4 cell counts that were below 200 cells/µl in the first year of ART. With this threshold, the potential savings in CD4 testing capacity was 54.3%. With a CD4 count threshold of 350 cells/µl, the potential savings in testing capacity was 34%. The results over a three-year follow-up were similar. When applied to six representative HIV-positive individuals, the tool correctly predicted all the CD4 counts above 200 cells/µl, although some individuals who had a predicted CD4 count of less than 200 cells/µl actually had a CD4 count above this threshold. Thus, none of these individuals would have been exposed to an undetected dangerous CD4 count, but the application of the tool would have saved 57% of the CD4 laboratory tests done during the first year of ART.
What Do These Findings Mean?
These findings support the use of this new tool—the prediction-based classification (PBC) algorithm—for predicting a drop in CD4 count below a clinically meaningful threshold in HIV-infected individuals receiving ART. Further studies are now needed to demonstrate the feasibility, clinical effectiveness, and cost-effectiveness of this approach, to find out whether the tool can be used over extended periods of time, and to investigate whether the accuracy of its predictions can be improved by, for example, adding in periodic CD4 testing. Provided these studies confirm its early promise, the researchers suggest that the PBC algorithm could be used as a “triage” tool to direct available laboratory testing capacity to high-priority individuals (those likely to have a dangerously low CD4 count). By optimizing the use of limited laboratory resources in this and other ways, the PBC algorithm could therefore help to maintain and expand ART programs in low- and middle-income countries.
Additional Information
Please access these web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001207.
Information is available from the US National Institute of Allergy and Infectious Diseases on HIV infection and AIDS
NAM/aidsmap provides basic information about HIV/AIDS and summaries of recent research findings on HIV care and treatment
Information is available from Avert, an international AIDS charity, on many aspects of HIV/AIDS, including information on HIV/AIDS treatment and care and on universal access to AIDS treatment (in English and Spanish)
The World Health Organization provides information about universal access to AIDS treatment (in several languages)
More information about universal access to HIV treatment, prevention, care, and support is available from UNAIDS
Patient stories about living with HIV/AIDS are available through Avert and through the charity website Healthtalkonline
doi:10.1371/journal.pmed.1001207
PMCID: PMC3328436  PMID: 22529752
9.  Metabolic and anthropometric parameters contribute to ART-mediated CD4+ T cell recovery in HIV-1-infected individuals: an observational study 
Background
The degree of immune reconstitution achieved in response to suppressive ART is associated with baseline individual characteristics, such as pre-treatment CD4 count, levels of viral replication, cellular activation, choice of treatment regimen and gender. However, the combined effect of these variables on long-term CD4 recovery remains elusive, and no single variable predicts treatment response. We sought to determine if adiposity and molecules associated with lipid metabolism may affect the response to ART and the degree of subsequent immune reconstitution, and to assess their ability to predict CD4 recovery.
Methods
We studied a cohort of 69 (48 females and 21 males) HIV-infected, treatment-naïve South African subjects initiating antiretroviral treatment (d4T, 3Tc and lopinavir/ritonavir). We collected information at baseline and six months after viral suppression, assessing anthropometric parameters, dual energy X-ray absorptiometry and magnetic resonance imaging scans, serum-based clinical laboratory tests and whole blood-based flow cytometry, and determined their role in predicting the increase in CD4 count in response to ART.
Results
We present evidence that baseline CD4+ T cell count, viral load, CD8+ T cell activation (CD95 expression) and metabolic and anthropometric parameters linked to adiposity (LDL/HDL cholesterol ratio and waist/hip ratio) significantly contribute to variability in the extent of CD4 reconstitution (ΔCD4) after six months of continuous ART.
Conclusions
Our final model accounts for 44% of the variability in CD4+ T cell recovery in virally suppressed individuals, representing a workable predictive model of immune reconstitution.
doi:10.1186/1758-2652-14-37
PMCID: PMC3163506  PMID: 21801351
10.  Randomized Trial of Time-Limited Interruptions of Protease Inhibitor-Based Antiretroviral Therapy (ART) vs. Continuous Therapy for HIV-1 Infection 
PLoS ONE  2011;6(6):e21450.
Background
The clinical outcomes of short interruptions of PI-based ART regimens remains undefined.
Methods
A 2-arm non-inferiority trial was conducted on 53 HIV-1 infected South African participants with viral load <50 copies/ml and CD4 T cell count >450 cells/µl on stavudine (or zidovudine), lamivudine and lopinavir/ritonavir. Subjects were randomized to a) sequential 2, 4 and 8-week ART interruptions or b) continuous ART (cART). Primary analysis was based on the proportion of CD4 count >350 cells(c)/ml over 72 weeks. Adherence, HIV-1 drug resistance, and CD4 count rise over time were analyzed as secondary endpoints.
Results
The proportions of CD4 counts >350 cells/µl were 82.12% for the intermittent arm and 93.73 for the cART arm; the difference of 11.95% was above the defined 10% threshold for non-inferiority (upper limit of 97.5% CI, 24.1%; 2-sided CI: −0.16, 23.1). No clinically significant differences in opportunistic infections, adverse events, adherence or viral resistance were noted; after randomization, long-term CD4 rise was observed only in the cART arm.
Conclusion
We are unable to conclude that short PI-based ART interruptions are non-inferior to cART in retention of immune reconstitution; however, short interruptions did not lead to a greater rate of resistance mutations or adverse events than cART suggesting that this regimen may be more forgiving than NNRTIs if interruptions in therapy occur.
Trial Registration
ClinicalTrials.gov NCT00100646
doi:10.1371/journal.pone.0021450
PMCID: PMC3125169  PMID: 21738668
11.  Association between HIV replication and serum leptin levels: an observational study of a cohort of HIV-1-infected South African women 
Background
Advanced HIV infection can result in lipoatrophy and wasting, even in the absence of ongoing opportunistic infections, suggesting that HIV may directly affect adipose tissue amount and distribution.
Methods
We assessed the relationship of fat (measured using anthropometry, DEXA, MRI scans) or markers related to glucose and lipid metabolism with viral load in a cross-sectional sample of 83 antiretroviral-naïve HIV-1-infected South African women. A multivariable linear model was fitted to log10VL to assess the combined effect of these variables.
Results
In addition to higher T cell activation, women with viral load greater than the population median had lower waist circumference, body mass index and subcutaneous abdominal fat, as well as lower serum leptin. We demonstrate that leptin serum levels are inversely associated with viral replication, independent of the amount of adipose tissue. This association is maintained after adjusting for multiple variables associated with disease progression (i.e., cellular activation and innate immunity effector levels).
Conclusions
Our results demonstrate that serum leptin levels are inversely associated with viral replication, independent of disease progression: we postulate that leptin may affect viral replication.
doi:10.1186/1758-2652-13-33
PMCID: PMC2941743  PMID: 20822522
12.  Circulating Monocytes in HIV-1-Infected Viremic Subjects Exhibit an Antiapoptosis Gene Signature and Virus- and Host-Mediated Apoptosis Resistance1 
Mechanisms that may allow circulating monocytes to persist as CD4 T cells diminish in HIV-1 infection have not been investigated. We have characterized steady-state gene expression signatures in circulating monocytes from HIV-infected subjects and have identified a stable antiapoptosis gene signature comprised of 38 genes associated with p53, CD40L, TNF, and MAPK signaling networks. The significance of this gene signature is indicated by our demonstration of cadmium chloride- or Fas ligand-induced apoptosis resistance in circulating monocytes in contrast to increasing apoptosis in CD4 T cells from the same infected subjects. As potential mechanisms in vivo, we show that monocyte CCR5 binding by HIV-1 virus or agonist chemokines serves as independent viral and host modulators resulting in increased monocyte apoptosis resistance in vitro. We also show evidence for concordance between circulating monocyte apoptosis-related gene expression in HIV-1 infection in vivo and available datasets following viral infection or envelope exposure in monocyte-derived macrophages in vitro. The identification of in vivo gene expression associated with monocyte resistance to apoptosis is of relevance to AIDS pathogenesis since it would contribute to: 1) maintaining viability of infection targets and long-term reservoirs of HIV-1 infection in the monocyte/macrophage populations, and 2) protecting a cell subset critical to host survival despite sustained high viral replication.
doi:10.4049/jimmunol.0801450
PMCID: PMC2776064  PMID: 19299747
14.  Low-Cost HIV-1 Diagnosis and Quantification in Dried Blood Spots by Real Time PCR 
PLoS ONE  2009;4(6):e5819.
Background
Rapid and cost-effective methods for HIV-1 diagnosis and viral load monitoring would greatly enhance the clinical management of HIV-1 infected adults and children in limited-resource settings. Recent recommendations to treat perinatally infected infants within the first year of life are feasible only if early diagnosis is routinely available. Dried blood spots (DBS) on filter paper are an easy and convenient way to collect and transport blood samples. A rapid and cost effective method to diagnose and quantify HIV-1 from DBS is urgently needed to facilitate early diagnosis of HIV-1 infection and monitoring of antiretroviral therapy.
Methods and Findings
We have developed a real-time LightCycler (rtLC) PCR assay to detect and quantify HIV-1 from DBS. HIV-1 RNA extracted from DBS was amplified in a one-step, single-tube system using primers specific for long-terminal repeat sequences that are conserved across all HIV-1 clades. SYBR Green dye was used to quantify PCR amplicons and HIV-1 RNA copy numbers were determined from a standard curve generated using serially diluted known copies of HIV-1 RNA. This assay detected samples across clades, has a dynamic range of 5 log10, and %CV <8% up to 4 log10 dilution. Plasma HIV-1 RNA copy numbers obtained using this method correlated well with the Roche Ultrasensitive (r = 0.91) and branched DNA (r = 0.89) assays. The lower limit of detection (95%) was estimated to be 136 copies. The rtLC DBS assay was 2.5 fold rapid as well as 40-fold cheaper when compared to commercial assays. Adaptation of the assay into other real-time systems demonstrated similar performance.
Conclusions
The accuracy, reliability, genotype inclusivity and affordability, along with the small volumes of blood required for the assay suggest that the rtLC DBS assay will be useful for early diagnosis and monitoring of pediatric HIV-1 infection in resource-limited settings.
doi:10.1371/journal.pone.0005819
PMCID: PMC2688035  PMID: 19503790
15.  Application of two machine learning algorithms to genetic association studies in the presence of covariates 
BMC Genetics  2008;9:71.
Background
Population-based investigations aimed at uncovering genotype-trait associations often involve high-dimensional genetic polymorphism data as well as information on multiple environmental and clinical parameters. Machine learning (ML) algorithms offer a straightforward analytic approach for selecting subsets of these inputs that are most predictive of a pre-defined trait. The performance of these algorithms, however, in the presence of covariates is not well characterized.
Methods and Results
In this manuscript, we investigate two approaches: Random Forests (RFs) and Multivariate Adaptive Regression Splines (MARS). Through multiple simulation studies, the performance under several underlying models is evaluated. An application to a cohort of HIV-1 infected individuals receiving anti-retroviral therapies is also provided.
Conclusion
Consistent with more traditional regression modeling theory, our findings highlight the importance of considering the nature of underlying gene-covariate-trait relationships before applying ML algorithms, particularly when there is potential confounding or effect mediation.
doi:10.1186/1471-2156-9-71
PMCID: PMC2620353  PMID: 19014573
16.  A likelihood-based approach to mixed modeling with ambiguity in cluster identifiers 
Biostatistics (Oxford, England)  2008;9(4):635-657.
This manuscript describes a novel, linear mixed-effects model–fitting technique for the setting in which correlated data indicators are not completely observed. Mixed modeling is a useful analytical tool for characterizing genotype–phenotype associations among multiple potentially informative genetic loci. This approach involves grouping individuals into genetic clusters, where individuals in the same cluster have similar or identical multilocus genotypes. In haplotype-based investigations of unrelated individuals, corresponding cluster assignments are unobservable since the alignment of alleles within chromosomal copies is not generally observed. We derive an expectation conditional maximization approach to estimation in the mixed modeling setting, where cluster assignments are ambiguous. The approach has broad relevance to the analysis of data with missing correlated data identifiers. An example is provided based on data arising from a cohort of human immunodeficiency virus type-1–infected individuals at risk for antiretroviral therapy–associated dyslipidemia.
doi:10.1093/biostatistics/kxm055
PMCID: PMC2536727  PMID: 18343883
Expectation conditional maximization; Genotype; Haplotype; HIV-1; Lipids; Missing identifiers; Mixed-effects models; Phenotype; Population-based genetic association studies
17.  Associations among Race/Ethnicity, ApoC-III Genotypes, and Lipids in HIV-1-Infected Individuals on Antiretroviral Therapy 
PLoS Medicine  2006;3(3):e52.
Background
Protease inhibitors (PIs) are associated with hypertriglyceridemia and atherogenic dyslipidemia. Identifying HIV-1-infected individuals who are at increased risk of PI-related dyslipidemia will facilitate therapeutic choices that maintain viral suppression while reducing risk of atherosclerotic diseases. Apolipoprotein C-III (apoC-III) gene variants, which vary by race/ethnicity, have been associated with a lipid profile that resembles PI-induced dyslipidemia. However, the association of race/ethnicity, or candidate gene effects across race/ethnicity, with plasma lipid levels in HIV-1-infected individuals, has not been reported.
Methods and Findings
A cross-sectional analysis of race/ethnicity, apoC-III/apoA-I genotypes, and PI exposure on plasma lipids was performed in AIDS Clinical Trial Group studies (n = 626). Race/ethnicity was a highly significant predictor of plasma lipids in fully adjusted models. Furthermore, in stratified analyses, the effect of PI exposure appeared to differ across race/ethnicity. Black/non-Hispanic, compared with White/non-Hispanics and Hispanics, had lower plasma triglyceride (TG) levels overall, but the greatest increase in TG levels when exposed to PIs. In Hispanics, current PI antiretroviral therapy (ART) exposure was associated with a significantly smaller increase in TGs among patients with variant alleles at apoC-III-482, −455, and Intron 1, or at a composite apoC-III genotype, compared with patients with the wild-type genotypes.
Conclusions
In the first pharmacogenetic study of its kind in HIV-1 disease, we found race/ethnic-specific differences in plasma lipid levels on ART, as well as differences in the influence of the apoC-III gene on the development of PI-related hypertriglyceridemia. Given the multi-ethnic distribution of HIV-1 infection, our findings underscore the need for future studies of metabolic and cardiovascular complications of ART that specifically account for racial/ethnic heterogeneity, particularly when assessing candidate gene effects.
This cross-sectional analysis of race/ethnicity, apoC-III/apoA-I genotypes, and protease inhibitor exposure on plasma lipids showed that race/ethnicity was a highly significant predictor of plasma lipids
doi:10.1371/journal.pmed.0030052
PMCID: PMC1334223  PMID: 16417409
18.  Randomized, Controlled Trial of Therapy Interruption in Chronic HIV-1 Infection 
PLoS Medicine  2004;1(3):e64.
Background
Approaches to limiting exposure to antiretroviral therapy (ART) drugs are an active area of HIV therapy research. Here we present longitudinal follow-up of a randomized, open-label, single-center study of the immune, viral, and safety outcomes of structured therapy interruptions (TIs) in patients with chronically suppressed HIV-1 infection as compared to equal follow-up of patients on continuous therapy and including a final therapy interruption in both arms.
Methods and Findings
Forty-two chronically HIV-infected patients on suppressive ART with CD4 counts higher than 400 were randomized 1:1 to either (1) three successive fixed TIs of 2, 4, and 6 wk, with intervening resumption of therapy with resuppression for 4 wk before subsequent interruption, or (2) 40 wk of continuous therapy, with a final open-ended TI in both treatment groups. Main outcome was analysis of the time to viral rebound (>5,000 copies/ml) during the open-ended TI. Secondary outcomes included study-defined safety criteria, viral resistance, therapy failure, and retention of immune reconstitution.
There was no difference between the groups in time to viral rebound during the open-ended TI (continuous therapy/single TI, median [interquartile range] = 4 [1–8] wk, n = 21; repeated TI, median [interquartile range] = 5 [4–8] wk, n = 21; p = 0.36). No differences in study-related adverse events, viral set point at 12 or 20 wk of open-ended interruption, viral resistance or therapy failure, retention of CD4 T cell numbers on ART, or retention of lymphoproliferative recall antigen responses were noted between groups. Importantly, resistance detected shortly after initial viremia following the open-ended TI did not result in a lack of resuppression to less than 50 copies/ml after reinitiation of the same drug regimen.
Conclusion
Cycles of 2- to 6-wk time-fixed TIs in patients with suppressed HIV infection failed to confer a clinically significant benefit with regard to viral suppression off ART. Also, secondary analysis showed no difference between the two strategies in terms of safety, retention of immune reconstitution, and clinical therapy failure. Based on these findings, we suggest that further clinical research on the long-term consequences of TI strategies to decrease drug exposure is warranted.
Structured treatment interruptions, or "drug holidays", in HIV patients yield no clinical benefits but don't lead to short- term treatment failure either
doi:10.1371/journal.pmed.0010064
PMCID: PMC539050  PMID: 15630469
19.  A murine model of myocardial microvascular thrombosis 
Journal of Clinical Investigation  1999;104(5):533-539.
Disorders of hemostasis lead to vascular pathology. Endothelium-derived gene products play a critical role in the formation and degradation of fibrin. We sought to characterize the importance of these locally produced factors in the formation of fibrin in the cardiac macrovasculature and microvasculature. This study used mice with modifications of the thrombomodulin (TM) gene, the tissue-type plasminogen activator (tPA) gene, and the urokinase-type plasminogen activator (uPA) gene. The results revealed that tPA played the most important role in local regulation of fibrin deposition in the heart, with lesser contributions by TM and uPA (least significant). Moreover, a synergistic relationship in fibrin formation existed in mice with concomitant modifications of tPA and TM, resulting in myocardial necrosis and depressed cardiac function. The data were fit to a statistical model that may offer a foundation for examination of hemostasis-regulating gene interactions.
PMCID: PMC408542  PMID: 10487767
20.  Latent variable modeling paradigms for genotype-trait association studies 
Characterizing associations among multiple single-nucleotide polymorphisms (SNPs) within and across genes, and measures of disease progression or disease status will potentially offer new insight into disease etiology and disease progression. However, this presents a significant analytic challenge due to the existence of multiple potentially informative genetic loci, as well as environmental and demographic factors, and the generally uncharacterized and complex relationships among them. Latent variable modeling approaches offer a natural framework for analysis of data arising from these population-based genetic association investigations of complex diseases as they are well-suited to uncover simultaneous effects of multiple markers. In this manuscript we describe application and performance of two such latent variable methods, namely structural equation models (SEMs) and mixed effects models (MEMs), and highlight their theoretical overlap. The relative advantages of each paradigm are investigated through simulation studies and, finally, an application to data arising from a study of anti-retroviral-associated dyslipidemia in HIV-infected individuals is provided for illustration.
doi:10.1002/bimj.201000218
PMCID: PMC3312474  PMID: 21887796
Mixed effects models; Single-nucleotide polymorphisms (SNPs); Structural equation model (SEM)

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