Christophe G Lambert

Christophe G Lambert
University of New Mexico | UNM · Center for Global Health

31.55
 · 
Ph.D.

About

93
Publications
6,771
Reads
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2,276
Citations
Introduction
Skills and Expertise
Research Experience
August 2014 - present
University of New Mexico
Position
  • Associate Professor
August 2013 - July 2014
Montana State University
Position
  • Research Professor
September 1998 - present
Golden Helix
Position
  • Founder & Chairman

Publications

Publications (93)
Article
Full-text available
Alendronate and raloxifene are among the most popular anti-osteoporosis medications. However, there is a lack of head-to-head comparative effectiveness studies comparing the two treatments. We conducted a retrospective large-scale multicenter study encompassing over 300 million patients across nine databases encoded in the Observational Medical Out...
Article
Full-text available
Background Hydroxychloroquine, a drug commonly used in the treatment of rheumatoid arthritis, has received much negative publicity for adverse events associated with its authorisation for emergency use to treat patients with COVID-19 pneumonia. We studied the safety of hydroxychloroquine, alone and in combination with azithromycin, to determine the...
Preprint
Full-text available
Introduction: Angiotensin converting enzyme inhibitors (ACEs) and angiotensin receptor blockers (ARBs) could influence infection risk of coronavirus disease (COVID-19). Observational studies to date lack pre-specification, transparency, rigorous ascertainment adjustment and international generalizability, with contradictory results. Methods: Using...
Preprint
Full-text available
Background: Hydroxychloroquine has recently received Emergency Use Authorization by the FDA and is currently prescribed in combination with azithromycin for COVID-19 pneumonia. We studied the safety of hydroxychloroquine, alone and in combination with azithromycin. Methods: New user cohort studies were conducted including 16 severe adverse events (...
Article
Full-text available
Objective: We aimed to impute uncoded self-harm in administrative claims data of individuals with major mental illness (MMI), characterize self-harm incidence, and identify factors associated with coding bias. Materials and methods: The IBM MarketScan database (2003-2016) was used to analyze visit-level self-harm in 10 120 030 patients with ≥2 M...
Article
Full-text available
Background: Severe malarial anemia (SMA) is a leading cause of malaria-related morbidity and mortality in children. The genetic factors that influence development of SMA and inefficient erythropoiesis, a central pathogenic feature of SMA, are only partially understood. Methods: We performed a pilot Genome-wide Association Study (GWAS) on childre...
Article
Full-text available
Objective: To compare the largest set of bipolar disorder pharmacotherapies to date (102 drugs and drug combinations) for risk of diabetes mellitus (DM). Methods: The IBM MarketScan® database was used to retrospectively analyze data on 565,253 adults with bipolar disorder without prior glucose metabolism-related diagnoses. The pharmacotherapies...
Article
Cyclooxygenase-2 [(COX-2) or prostaglandin endoperoxide H2 synthase-2 (PTGS-2)] induces the production of prostaglandins as part of the host-immune response to infections. Although a number of studies have demonstrated the effects of COX-2 promoter variants on autoimmune and inflammatory diseases, their role in malaria remains undefined. As such, w...
Article
Full-text available
Background: Severe malarial anaemia (SMA) is a leading cause of childhood mortality in holoendemic Plasmodium falciparum regions. Methods: To gain an improved understanding of SMA pathogenesis, whole genome and transcriptome profiling was performed in Kenyan children (n=144, 3-36months) with discrete non-SMA and SMA phenotypes. Leukocyte associa...
Article
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Background: Leukocyte-associated immunoglobulin like receptor-1 (LAIR1) is a transmembrane inhibitory receptor that influences susceptibility to a myriad of inflammatory diseases. Our recent investigations of severe malarial anaemia (SMA) pathogenesis in Kenyan children discovered that novel LAIR1 genetic variants which were associated with decrea...
Article
Full-text available
Background: This study compared the largest set of bipolar disorder pharmacotherapies to date (71 drugs and drug combinations) for risk of kidney disorders (KDs). Methods: This retrospective observational study used the IBM MarketScan® database to analyze data on 591,052 adults with bipolar disorder without prior nephropathy, for onset of KDs (o...
Preprint
Full-text available
BACKGROUND Patient education has taken center stage in successfully shared decision-making between patients and health care providers; however, very little is known about how patients typically obtain information on their illness, especially as it relates to the treatment of bipolar disorder and what methods of information sharing are preferred. O...
Article
Full-text available
Background: Patient education has taken center stage in successfully shared decision making between patients and health care providers. However, little is known about how patients with bipolar disorder typically obtain information on their illness and the treatment options available to them. Objective: This study aimed to obtain the perspectives...
Article
Full-text available
Objectives This study compared 29 drugs for risk of psychiatric hospitalization in bipolar disorders, addressing the evidence gap on the >50 drugs used by US patients for treatment. Methods The Truven Health Analytics MarketScan® database was used to identify 190 894 individuals with bipolar or schizoaffective disorder who filled a prescription fo...
Poster
Full-text available
We present one of the largest reported retrospective observational study on drug-dependent risk of hospitalization in bipolar spectrum disorders, funded by the Patient-Centered Outcomes Research Institute (CER-1507-3160). The data were obtained from the Truven Health Analytics MarketScan® administrative claims database, transformed to the OMOP comm...
Poster
Full-text available
Patients suffering from bipolar disorder have an increased risk of attempting self-harm/suicide by numerous means. Although many suicidal patients are hospitalized for diagnosis and treatment, the vast majority of such visits are not documented with suicidality/selfharm diagnostic codes in administrative claims data, which makes studies related to...
Poster
Full-text available
Innovations to the R package LocalControl are presented. The package implements nonparametric approaches to address biases and confounding when comparing treatments or exposures inobservational studies. This work illustrates how LocalControl can address the problem of feature selection, and how it can provide bias corrected insight into what variab...
Article
Full-text available
Objectives: As part of a series of Patient-Centered Outcomes Research Institute-funded large-scale retrospective observational studies on bipolar disorder (BD) treatments and outcomes, we sought the input of patients with BD and their family members to develop research questions. We aimed to identify systemic root causes of patient-reported challe...
Article
Full-text available
Introduction Chromosomal microarray analysis (CMA) is recognized as the first-tier test in the genetic evaluation of children with developmental delays, intellectual disabilities, congenital anomalies and autism spectrum disorders of unknown etiology. Array Design To optimize detection of clinically relevant copy number variants associated with th...
Book
Human Genome Informatics: Translating Genes into Health examines the most commonly used electronic tools for translating genomic information into clinically meaningful formats. By analyzing and comparing interpretation methods of whole genome data, the book discusses the possibilities of their application in genomic and translational medicine. Topi...
Article
Full-text available
Background: Bipolar disorder refers to a group of chronic psychiatric disorders of mood and energy levels. While dramatic psychiatric symptoms dominate the acute phase of the diseases, the chronic course is often determined by an increasing burden of co-occurring medical conditions. High rates of diabetes mellitus in patients with bipolar disorder...
Poster
Full-text available
We announce the availability of a public OMOP Common Data Model v5 (CDMv5) dataset containing 2.33 million synthetic patients from the Centers for Medicare & Medicaid Services (CMS) Data Entrepreneurs’ Synthetic Public Use File (DE-SynPUF). We anticipate that this resource will be useful for researchers in developing OHDSI tools, as well as serve a...
Article
Full-text available
Objectives Thyroid abnormalities in patients with bipolar disorder (BD) have been linked to lithium treatment for decades, yet other drugs have been less well studied. Our objective was to compare hypothyroidism risk for lithium versus the anticonvulsants and second‐generation antipsychotics commonly prescribed for BD. Methods Administrative claim...
Article
Full-text available
Background: Wolf-Hirschhorn syndrome (WHS) is a contiguous gene deletion syndrome involving variable size deletions of the 4p16.3 region. Seizures are frequently, but not always, associated with WHS. We hypothesised that the size and location of the deleted region may correlate with seizure presentation. Methods: Using chromosomal microarray ana...
Article
Full-text available
It is well-known that claims coming from observational studies often fail to replicate when rigorously re-tested. The technical problems include multiple testing, multiple modeling and bias. Any or all of these problems can give rise to claims that will fail to replicate. There is a need for statistical methods that are easily applied, are easy to...
Article
Full-text available
The entire drug safety enterprise has a need to search, retrieve, evaluate, and synthesize scientific evidence more efficiently. This discovery and synthesis process would be greatly accelerated through access to a common framework that brings all relevant information sources together within a standardized structure. This presents an opportunity to...
Article
Full-text available
Genetics clearly plays a major role in the etiology of autism spectrum disorders (ASDs), but studies to date are only beginning to characterize the causal genetic variants responsible. Until recently, studies using multiple extended multi-generation families to identify ASD risk genes had not been undertaken. We identified haplotypes shared among i...
Article
Full-text available
Structural variation is thought to play a major etiological role in the development of autism spectrum disorders (ASDs), and numerous studies documenting the relevance of copy number variants (CNVs) in ASD have been published since 2006. To determine if large ASD families harbor high-impact CNVs that may have broader impact in the general ASD popul...
Data
Supplemental data Tables S1–S4. Table S1. TaqMan assays used for CNV confirmation. Genomic coordinates and assay names for all TaqMan assays used for CNV confirmation. All coordinates are shown using hg19 coordinates. Table S2. CNVs identified in Utah ASD families. The chromosomal locations and copy number status of all CNVs identified in Utah ASD...
Data
Supplemental methods and results. Supplemental methods. Details regarding sources of DNA samples used, methods for array processing, and sample quality control are described. Supplemental results. Analysis of population stratification using principal component analysis. The only samples used in CNV analyses were those demonstrated to be within the...
Article
Full-text available
During the last several years, high-density genotyping SNP arrays have facilitated genome-wide association studies (GWAS) that successfully identified common genetic variants associated with a variety of phenotypes. However, each of the identified genetic variants only explains a very small fraction of the underlying genetic contribution to the stu...
Data
Concordance of genotypes between technical replicates from genotyping experiment E2 by using Affy6 platform. Each column and each row represent a technical replicate of a sample indicated by the sample codes at the x-axis and y-axis that are listed in Table 1. (DOC)
Data
Concordance of genotypes between technical replicates from genotyping experiment E1 by using Affy6 platform. Each column and each row represent a technical replicate of a sample indicated by the sample codes at the x-axis and y-axis that are listed in Table 1. (DOC)
Data
Concordance of genotypes between technical replicates from genotyping experiment E3 by using Affy6 platform. Each column and each row represent a technical replicate of a sample indicated by the sample codes at the x-axis and y-axis that are listed in Table 1. (DOC)
Data
Concordance of genotypes between technical replicates from genotyping experiment E5 by using Illu1M platform. Each column and each row represent a technical replicate of a sample indicated by the sample codes at the x-axis and y-axis that are listed in Table 1. (DOC)
Data
Layout of samples on the plates and corresponding information. (DOC)
Data
Concordance of genotypes between technical replicates from genotyping experiment E4 by using Illu1M platform. Each column and each row represent a technical replicate of a sample indicated by the sample codes at the x-axis and y-axis that are listed in Table 1. (DOC)
Data
Concordance of genotypes between technical replicates from genotyping experiment E1 and experiment E2 by using Affy6 platform. Each column and each row represent a technical replicate of a sample indicated by the sample codes at the x-axis (genotyping experiment E2) and y-axis (genotyping experiment E1) that are listed in Table 1. (DOC)
Data
Concordance of genotypes between technical replicates from genotyping experiment E4 and experiment E5 by using Illu1M platform. Each column and each row represent a technical replicate of a sample indicated by the sample codes at the x-axis (genotyping experiment E5) and y-axis (genotyping experiment E4) that are listed in Table 1. (DOC)
Data
Concordance of genotypes between technical replicates from genotyping experiment E1 by using Affy6 platform and experiment E5 by using Illu1M platform. Each column and each row represent a technical replicate of a sample indicated by the sample codes at the x-axis (genotyping experiment E5) and y-axis (genotyping experiment E1) that are listed in T...
Data
Concordance of genotypes between technical replicates from genotyping experiment E3 by using Affy6 platform and experiment E4 by using Illu1M platform. Each column and each row represent a technical replicate of a sample indicated by the sample codes at the x-axis (genotyping experiment E4) and y-axis (genotyping experiment E3) that are listed in T...
Data
QC results of raw data from Affymetrix platform. Blue bars are for samples from genotyping experiment E2, red bars are for samples from genotyping experiment E1, and cyan bars are for samples from genotyping experiment E3. (DOC)
Data
QC results of raw data from Illumina platform. Red circles are for samples from genotyping experiment E4 and black are for samples from genotyping experiment E5. (DOC)
Data
Concordance of genotypes between technical replicates from genotyping experiment E2 and experiment E3 by using Affy6 platform. Each column and each row represent a technical replicate of a sample indicated by the sample codes at the x-axis (genotyping experiment E3) and y-axis (genotyping experiment E2) that are listed in Table 1. (DOC)
Data
Concordance of genotypes between technical replicates from genotyping experiment E2 by using Affy6 platform and experiment E4 by using Illu1M platform. Each column and each row represent a technical replicate of a sample indicated by the sample codes at the x-axis (genotyping experiment E4) and y-axis (genotyping experiment E2) that are listed in T...
Data
Concordance of genotypes between technical replicates from genotyping experiment E2 by using Affy6 platform and experiment E5 by using Illu1M platform. Each column and each row represent a technical replicate of a sample indicated by the sample codes at the x-axis (genotyping experiment E5) and y-axis (genotyping experiment E2) that are listed in T...
Data
Concordance of genotypes between technical replicates from genotyping experiment E3 by using Affy6 platform and experiment E5 by using Illu1M platform. Each column and each row represent a technical replicate of a sample indicated by the sample codes at the x-axis (genotyping experiment E5) and y-axis (genotyping experiment E3) that are listed in T...
Data
Successful genotype call rates for 24 NDA replicates of the six subjects are represented by bars (left y-axis) color coded by subject. Red: HapMap NA10385; Black and Blue: HapMap NA12249; Magenta: HapMap NA12248; Cyan: NCTR59; Yellow: NCTR8; Green: NCTR13. Heterozygote call rates (right y-axis) are plotted as solid circles and overlaid onto the cor...
Data
Concordance of genotypes between technical replicates from genotyping experiment E2 by using Affy6 platform with the replicates of low quality of included. Each column and each row represent a technical replicate of a sample indicated by the sample codes at the x-axis and y-axis that are listed in Table 1. (DOC)
Data
Simulations results (Sample size = 10,000: case: 5,000; control: 5,000). (DOC)
Data
Concordance of genotypes between technical replicates from genotyping experiments by using Affy6 platform. For HapMap subject NA10835 (A), there are 13 rows and columns: the first four are from genotyping experiment E1; the second four are from genotyping experiment E2; the third four are from genotyping experiment E3; and the last one is from HapM...
Data
Concordance of genotypes between technical replicates from genotyping experiment E1 and experiment E3 by using Affy6 platform. Each column and each row represent a technical replicate of a sample indicated by the sample codes at the x-axis (genotyping experiment E3) and y-axis (genotyping experiment E1) that are listed in Table 1. (DOC)
Data
Concordance of genotypes between technical replicates from genotyping experiment E1 by using Affy6 platform and genotyping experiment E4 by using Illu1M platform. Each column and each row represent a technical replicate of a sample indicated by the sample codes at the x-axis (genotyping experiment E4) and y-axis (genotyping experiment E1) that are...
Data
Successful genotype call rates for 24 NDA replicates of the six subjects are represented by bars (left y-axis) color coded by subject. Red: HapMap NA10385; Blue: HapMap NA12249; Magenta: HapMap NA12248; Cyan: NCTR59; Yellow: NCTR8; Green: NCTR13. Heterozygote call rates (right y-axis) are plotted as solid circles and overlaid onto the corresponding...
Data
Concordance of genotypes between technical replicates from genotyping experiment E1 by using Affy6 platform with the replicate of low quality of included. Each column and each row represent a technical replicate of a sample indicated by the sample codes at the x-axis and y-axis that are listed in Table 1. (DOC)
Data
Concordance of genotypes between technical replicates from genotyping experiments by using Illu1M platform. For each of the three HapMap subjects, there are nine rows and columns. The first four represent genotyping results from genotyping experiment E4, the second four are referred to genotyping results from genotyping experiment E5, and the last...
Data
Simulations results (Sample size = 10,000: case: 5,000; control: 5,000). (DOC)
Article
Full-text available
Many public and private genome-wide association studies that we have analyzed include flaws in design, with avoidable confounding appearing as a norm rather than the exception. Rather than recognizing flawed research design and addressing that, a category of quality-control statistical methods has arisen to treat only the symptoms. Reflecting more...
Data
The supporting information provides the counts and proportions of the latent class solutions and the Bayesian information criteria, on which the latent class solution was selected. The QQ plot for the genome-wide association analysis under the recessive model is provided, followed by scatter plots for the genome-wide significant genotypes, first af...
Article
Full-text available
Bipolar disorder is a severe psychiatric disorder with high heritability. Co-morbid conditions are common and might define latent subgroups of patients that are more homogeneous with respect to genetic risk factors. In the Caucasian GAIN bipolar disorder sample of 1000 cases and 1034 controls, we tested the association of single nucleotide polymorp...
Article
Full-text available
To enable the assessment of compound heterozygosity, we propose a simple approach for incorporating genotype phase in a rare variant collapsing procedure for the analysis of DNA sequence data. When multiple variants are identified within a gene, knowing the phase of each variant may provide additional statistical power to detect associations with p...
Article
Full-text available
The Genome-Wide Association Working Group (GWAWG) is part of a large-scale effort by the MicroArray Quality Consortium (MAQC) to assess the quality of genomic experiments, technologies and analyses for genome-wide association studies (GWASs). One of the aims of the working group is to assess the variability of genotype calls within and between diff...
Article
Full-text available
The Affymetrix GeneChip Human Mapping 500K array is common for genome-wide association studies (GWASs). Recent findings highlight the importance of accurate genotype calling algorithms to reduce the inflation in Type I and Type II error rates. Differential results due to genotype calling errors can introduce severe bias in case-control association...
Article
Full-text available
The robustness of genome-wide association study (GWAS) results depends on the genotyping algorithms used to establish the association. This paper initiated the assessment of the impact of the Corrected Robust Linear Model with Maximum Likelihood Classification (CRLMM) genotyping quality on identifying real significant genes in a GWAS with large sam...
Article
Full-text available
Gene expression data from microarrays are being applied to predict preclinical and clinical endpoints, but the reliability of these predictions has not been established. In the MAQC-II project, 36 independent teams analyzed six microarray data sets to generate predictive models for classifying a sample with respect to one of 13 endpoints indicative...