Doctor of Philosophy, University of California, Berkeley, Environmental Health Sciences & Designated Emphasis in Computational and Genomic Biology (2022)
Master of Public Health, University of California, Berkeley, Environmental Health Sciences (2019)
Bachelor of Science, University of California, Davis, Environmental Toxicology & Minor in Communication (2016)
Andres Cardenas, Postdoctoral Faculty Sponsor
Associations of Prenatal First Trimester Essential and Nonessential Metal Mixtures with Body Size and Adiposity in Childhood.
Epidemiology (Cambridge, Mass.)
2023; 34 (1): 80-89
Prenatal nonessential metals may contribute to postnatal adiposity, whereas essential metals may have metabolic benefits. We evaluated joint and individual associations between prenatal metals and childhood adiposity.We measured concentrations of six nonessential (arsenic, barium, cadmium, cesium, lead, and mercury) and four essential (magnesium, manganese, selenium, and zinc) metals in first trimester maternal blood from a prebirth cohort. We collected anthropometric measures in early childhood, mid-childhood, and early adolescence including subscapular+tricep skinfold thickness (mm) (N = 715-859), waist circumference (cm) (N = 717-882), and body mass index (BMI) (z-score) (N = 716-875). We measured adiposity in mid-childhood and early adolescence using bone densitometry total- and trunk- fat mass index (kg/m2) (N = 511-599). We estimated associations using adjusted quantile g-computation and linear regression.The nonessential metal mixture was associated with higher total (β = 0.07, 95% CI = 0.01, 0.12) and trunk fat mass index (β = 0.12, CI = 0.02, 0.22), waist circumference (β = 0.01, CI = 0.00, 0.01), and BMI (β = 0.24, CI = 0.07, 0.41) in mid-childhood, and total fat mass index (β = 0.07, CI = 0.01, 0.14), and BMI (β = 0.19, CI = 0.02, 0.37) in early adolescence. The essential metal mixture was associated with lower early adolescence total-(β = -0.11, CI = -0.17, -0.04) and trunk- fat mass index (β = -0.13, CI = -0.21, -0.05), subscapular+tricep skinfold thickness (β = -0.02, CI = -0.03, -0.00), waist circumference (β = -0.003, CI = -0.01, -0.00), and BMI (β = -0.16, CI = -0.28, -0.04). Cadmium and cesium were individually associated with childhood adiposity at different timepoints.Prenatal first-trimester essential metals were associated with lower childhood adiposity, whereas nonessential metals were associated with higher adiposity into adolescence.
View details for DOI 10.1097/EDE.0000000000001560
View details for PubMedID 36455248
Comparison of DNA methylation measurements from EPIC BeadChip and SeqCap targeted bisulphite sequencing in PON1 and nine additional candidate genes
Epigenome-wide association studies (EWAS) are widely implemented in epidemiology, and the Illumina HumanMethylationEPIC BeadChip (EPIC) DNA microarray is the most-used technology. Recently, next-generation sequencing (NGS)-based methods, which assess DNA methylation at single-base resolution, have become more affordable and technically feasible. While the content of microarray technology is fixed, NGS-based approaches, such as the Roche Nimblegen, SeqCap Epi Enrichment System (SeqCap), offer the flexibility of targeting most CpGs in a gene. With the current usage of microarrays and emerging NGS-based technologies, it is important to establish whether data generated from the two platforms are comparable. We harnessed 112 samples from the Center for the Health Assessment of Mothers and Children of Salinas (CHAMACOS) birth cohort study and compared DNA methylation between the EPIC microarray and SeqCap for PON1 and nine additional candidate genes, by evaluating epigenomic coverage and correlations. We conducted multivariable linear regression and principal component analyses to assess the ability of the EPIC array and SeqCap to detect biological differences in gene methylation by the PON1-108 single nucleotide polymorphism. We found an overall high concordance (r = 0.84) between SeqCap and EPIC DNA methylation, among highly methylated and minimally methylated regions. However, substantial disagreement was present between the two methods in moderately methylated regions, with SeqCap measurements exhibiting greater within-site variation. Additionally, SeqCap did not capture PON1 SNP associated differences in DNA methylation that were evident with the EPIC array. Our findings indicate that microarrays perform well for analysing DNA methylation in large cohort studies but with limited coverage.
View details for DOI 10.1080/15592294.2022.2091818
View details for Web of Science ID 000820075200001
View details for PubMedID 35786310