Andric Ortiz, MD MPH - Massachusetts General Hospital - Research Fellow

Andric Ortiz

MD MPH

Massachusetts General Hospital

Research Fellow

Boston, Massachusetts | United States

Main Specialties: Biochemical Genetics, Medical Genetics, Ophthalmology, Public Health, Statistics, Surgery

Additional Specialties: Transplantation

ORCID logohttps://orcid.org/0000-0003-0731-2464


Top Author

Andric Ortiz, MD MPH - Massachusetts General Hospital - Research Fellow

Andric Ortiz

MD MPH

Introduction

Medical Doctor degree from Universidad Panamericana School of Medicine and Master in Public Health at Yale University. Currently working in transplant surgery, genetic epidemiology (especially pharmacogenetics-genomics), clinical and basic research science, and translational medicine.

Primary Affiliation: Massachusetts General Hospital - Boston, Massachusetts , United States

Specialties:

Additional Specialties:

Research Interests:


View Andric Ortiz’s Resume / CV

Education

May 2016 - May 2017
Yale University Yale School of Public Health
MPH
Jun 2010 - Jun 2016
Universidad Panamericana - Campus México
MD
School of Medicine

Experience

May 2016
Honors. Universidad Panamericana, School of Medicine
May 2016
Overlook International Foundation Scholarship
Grant Receiver

Publications

8Publications

259Reads

158Profile Views

1PubMed Central Citations

Veterans' compensation claims beliefs predict timing of PTSD treatment use relative to compensation and pension exam.

PLoS One 2018 27;13(12):e0209488. Epub 2018 Dec 27.

Department of Psychiatry, Yale University, New Haven, CT, United States of America.

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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0209488PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6307722PMC
December 2018
175 Reads
3.234 Impact Factor

Identification of potential genomic biomarkers predictors for preeclampsia risk: a systematic review and meta-analysis

PROSPERO 2018 CRD42018090519

PROSPERO International prospective register of systematic reviews

Citation

Andric Christopher Perez-Ortiz, Eugenia Moran-Orozco, Benito Estrada-Mena, Aimee Dominguez-Nieto, Esmeralda Lira-Romero, Maria Fernanda Ortega-Treviño, Jorge Arturo Izquierdo-Limon, Valeria Sandoval-Martinez, Eduardo Saad-Canales, Daniela Gutierrez-Arredondo, David Jimenez-Collado, Salvador Jimenez-Chaidez, Francisco Javier Estrada-Mena. Identification of potential genomic biomarkers predictors for preeclampsia risk: a systematic review and meta-analysis. PROSPERO 2018 CRD42018090519 Available from: http://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42018090519

Review question

P: Pregnant women, gestational age greater than 20 weeks and 12 weeks postpartum.
I: Genomic biomarkers (including SNPs, miRNAs, CNVs, etc.) (Minor allele carriers considered as exposed)
C: Major allele carriers (Taken as unexposed).
O: Risk of pre-eclampsia phenotypes (PE, PE with severe symptoms, and eclampsia).
In pregnant and puerperal women diagnosed with any phenotype of preeclampsia-eclampsia, does any genomic biomarker (e.g., SNP, CNV, indel, miRNA) significantly influence the probability of being diagnosed? Additionally, is any biomarker associated with a severe phenotype?

Searches

We are conducting a systematic search in MEDLINE, EMBASE, HuGENET, LILACS, ProQuest, and PubMed databases without any language restrictions. A priori, we established a comprehensive matrix of search including control vocabulary and boolean/logic operators. We will include observational studies of all phenotypes of pre-eclampsia (PE) (PE, PE with severe symptoms, and eclampsia) from women around 20 gestational weeks and puerperium. Included studies should follow the tenants of Helsinki and follow the diagnostic guidelines of the American College of Obstetricians and Gynecologists (ACOG). All genotype data must be determined with validated genotyping instruments and should reflect a stringent quality check (e.g., genotyping call rate ≥ 95%, Hardy-Weinberg equilibrium in controls, etc.). We will abstract critical demographics and number of PE cases and controls with a given genotype. Our primary outcome will be the proportions of all PE phenotypes based on their genotype. Proportions of gestational hypertension and HELLP syndrome and serum biomarkers will be secondary goals. We will perform a meta-analysis of these measurements using random and fixed effects models. Additionally, we will examine inter-study heterogeneity with a meta-regression model.

Types of study to be included

All observational studies and randomized controlled trials if applicable are going to be considered for this review. Abstracts and full published reports will be examined to create a comprehensive list of all current genomic markers for PE (additionally for HELLP and/or gestational hypertension, see Secondary outcomes). To avoid information bias, we will include all studies with a valid genotyping methodology and results in duplicate from blinded technicians. To decrease the risk of selection bias in our estimates, all studies must follow current preeclampsia diagnostic guidelines endorsed by the American College of Obstetricians and Gynecologists (ACOG) and have a full description of their cases and controls.

Condition or domain being studied

Preeclampsia (PE) refers to the new onset of hypertension and proteinuria, or hypertension and end-organ dysfunction with or without proteinuria after 20 weeks of gestation up to 12 weeks postpartum in a previously normotensive woman (it may also refer to worsening blood pressure and proteinuria in women with a history of chronic pre-pregnancy hypertension). This disorder is caused by placental and maternal vascular dysfunction, which includes deficient trophoblast invasion of the endometrium and myometrium, and defective remodeling of the spiral arteries during the 18-20th weeks of gestation. These defects cause poor placental perfusion and ischemic lesions. Ischemic and dysfunctional endothelial cells produce altered quantities of vasoactive mediators (which causes pathological vasoconstriction) and proinflammatory factors.

PE may affect up to 4.6% of pregnant women worldwide. Though affected women will most likely fully recover after the delivery or 12 weeks postpartum at the most, they can also experience several life-threatening complications such as eclampsia (additional development of seizures, in the absence of other neurological predisposing conditions), HELLP syndrome (hemolysis, elevated liver enzymes, and low platelet count), placental abruption, preterm birth, and death (preeclampsia/eclampsia account for 10-15% of direct maternal deaths). Although multiple risk factors have already been discovered through clinical and large cohort studies, the molecular underpinnings are currently unknown. Nevertheless, PE has a clear genetic component. Women whose mothers had preeclampsia were more likely to have the condition in their pregnancies and men born after a pregnancy complicated by preeclampsia were more likely to father a pregnancy complicated by preeclampsia. Also, for both women and men, familial preeclampsia was associated with more severe preeclampsia in the index pregnancy.

Participants/population

We will include publications that evaluate pregnant women from week 20 of pregnancy until 12 weeks postpartum. The following parameters need to follow current diagnostic recommendations or guidelines endorsed by the ACOG/AHA:

1. Hypertension should be defined as either a systolic blood pressure of 140 mm Hg or greater, a diastolic of 90 mm Hg or greater or both. The diagnosis requires at least two determinations 4 hours apart each. The optimal measurement of the blood pressure must be made with the patient seated, legs uncrossed, with arms and back supported, relaxed and not talking during the procedure. If elevated on the initial assessment the measurement should be repeated after several minutes.
2. Proteinuria should be defined with excretion of 300 mg in 24 hours or the ratio protein/creatinine in a single voided urine of 0.3 mg/dl or a qualitative dipstick reading of 30 mg/dL.
3. Preeclampsia is a multisystemic syndrome which develops hypertension in the second half of pregnancy in previously normotensive women. The new-onset of proteinuria is often associated, but in its absence, hypertension with end-organ dysfunction with new-onset of any of the following may confirm the diagnosis; sudden manifestation of signs and symptoms (right upper quadrant pain, severe headaches or visual disturbances, pulmonary edema), or a biochemical alterations (impaired liver enzymes, platelet levels below 100,000/microliter, creatinine level doubled or above 1.1 in women without other renal disease and a sustained increase in protein excretion) or blood pressure greater than or equal to 160 mm Hg systolic or greater than or equal to 110 mm Hg systolic hypertension.
4. Eclampsia should be defined as the presence of new-onset of grand mal seizures in women with preeclampsia. It may occur before, during or after labor.
5. Chronic hypertension is defined as a high blood pressure that preceded the conception, or that is diagnosed before 20 weeks of gestation, or that persist longer than 12 weeks postpartum.
6. Preeclampsia may complicate other hypertensive disorders; the diagnosis of chronic hypertension with superimposed preeclampsia is made in a patient with chronic hypertension that develops a new-onset of proteinuria, exacerbation of hypertension, or any manifestation of signs, symptoms or biochemical alterations of preeclampsia.
7. Gestational hypertension should be defined as a new-onset of elevated blood pressure after 20 weeks of gestation, often near term, in the absence of proteinuria.

Intervention(s), exposure(s)

We will include observational studies that determine genotype based on validated genotyping instruments and all results are corroborated by triplicate from blinded experienced operators. Preeclampsia phenotypes must follow the ACOG guidelines.

Comparator(s)/control

All observational studies that determines genotype based phenotypes of PE are going to be considered for this review. For determining cases included studies should follow diagnostic guidelines of the ACOG. 

Context

Main outcome(s)

The primary outcome will be the proportions of all PE phenotypes based on their genotype. For assessing severity, studies done before 2013, we will abstract such data following the previous classification (mild PE, severe PE, eclampsia). Studies after 2013 should follow the new diagnostic guideline (PE with/without severe symptoms, eclampsia) to be considered for review.

Additional outcome(s)

Enlisting all genomic biomarkers currently researched (e.g., SNP, CNV, indel, miRNA, etc.) will be a secondary outcome of this systematic review. Additionally, we will aim to determine the usefulness of such biomarkers in gestational hypertension and HELLP syndrome.

Data extraction (selection and coding)

Data will be collected based on a standardized format of the STREGA recommendations for reporting genetic association studies (Little et al., 2009) and published evidence on likely variables of interest in genetic epidemiology (Sagoo, Little, & Higgins, 2009). Extracted data will include study design (such as GWAS, cohort, case-control, cross-sectional), statement regarding if the study is the first report of a genetic association, a replication effort, or both, definition of PE cases, description of the laboratory methods including source, storage and genotyping approaches and platforms, sample size calculation, essential descriptive data, main outcome of interests (genotypes, phenotypes and other exposures) and measures of association (OR, HR, RR with appropriate 95% confidence interval). Each reviewer will independently assess each paper for data collection and extraction. Similarly, any disagreements will be consulted with a third field expert reviewer. 

Risk of bias (quality) assessment

Bias will be assessed based on the updated Cochrane Back Review Group criteria. As this protocol concerns genetic epidemiology selection bias regarding phenotype or genotype information will include whether cases have been appropriately diagnosed, or even excluding familial or syndromic cases. Also, regarding information bias, all studies must prove results in duplicate. Bias will be independently assessed by five reviewers, in the event of disagreement a third expert reviewer will be consulted.

Strategy for data synthesis

If possible, relatively homogenous results (I² less than 75%) will be combined and analyzed through meta-analysis. Forest plots will be drafted to evidence the individual effect of each genetic biomarker on PE diagnosis. The quality of each study will be assessed according to the guidelines for reporting genetic biomarkers adapted for this study (Altman, McShane, Sauerbrei, & Taube, 2012) and the STREGA recommendations (Little et al., 2009).

Analysis of subgroups or subsets

Clinical diversity can be encountered if some observational studies differ in setting, participants (especially different races/ethnicities with differential genome pattern), or even outcome measure (ascertainment of the diagnosis based on other recommendations than the ACOG). The above might lead to statistical heterogeneity increased in this type of genetic association studies by conflicting evidence among subsets of the population. To assess heterogeneity a χ² test at the 0.05 level of significance will be used. I² values greater than 75% will be considered highly heterogeneous, between 25-75% moderately and less than 25% comparable. Highly heterogeneous studies will be analyzed using a random-effects model, the rest with a fixed-effect model. Additionally, we will perform a meta-regression model to address any statistically significant heterogeneity adjusting for the journal, inter-study, and clinical parameters.

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December 2018
2 Reads

Significant Association Between Variant in SGCD and Age-Related Macular Degeneration.

Genes (Basel) 2018 Sep 25;9(10). Epub 2018 Sep 25.

Laboratorio de Biología Molecular, Escuela de Medicina, Universidad Panamericana, Donatello 59 Insurgentes Mixcoac Benito Juárez 03920 Ciudad de México, Mexico.

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http://dx.doi.org/10.3390/genes9100467DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6210939PMC
September 2018
20 Reads

Dysregulation of mitochondrial function and biogenesis modulators in adipose tissue of obese children.

Int J Obes (Lond) 2018 04 21;42(4):618-624. Epub 2017 Nov 21.

Sección de Estudios de Posgrado e Investigación, Escuela Superior de Medicina, Instituto Politécnico Nacional, Ciudad de Mexico, México.

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http://dx.doi.org/10.1038/ijo.2017.274DOI Listing
April 2018
2 Reads
1 Citation
5.004 Impact Factor

Pharmacogenetic markers predictors of response to treatment for primary open angle glaucoma: a systematic review and meta-analysis

PROSPERO 2018 CRD42018082612

PROSPERO International prospective register of systematic reviews

Citation

Andric Perez-Ortiz, David Jimenez-Collado, Alvaro Rendon, Claudia Palacio-Pastrana, Claudia Zepeda-Palacio, Salvador Jimenez-Chaidez, Bani Antonio-Aguirre, Francisco Javier Estrada-Mena. Pharmacogenetic markers predictors of response to treatment for primary open angle glaucoma: a systematic review and meta-analysis. PROSPERO 2018 CRD42018082612 Available from: http://www.crd.york.ac.uk/PROSPERO/display_record.php?ID=CRD42018082612

Review question

In the setting of primary open angle glaucoma, do major allele carriers of pharmacogenetic biomarkers compared to minor allele carriers achieve a differential response rate in intraocular pressures (IOP) to IOP-lowering drugs?

Searches

We are conducting a systematic search in MEDLINE, HuGENET, LILACS, and PubMed databases. We will include observational studies that determine genotype based on validated genotyping instruments and with a stringent quality check (e.g., genotyping call rate ≥ 95%, Hardy-Weinberg equilibrium in controls). We will collect mean and standard deviation of the percent IOP reduction (%ΔIOP) or mean intraocular pressure among responders and non-responders to IOP-lowering groups based on genotype information. We will perform a meta-analysis of these measurements using random and fixed effects models.

Types of study to be included

All observational studies, genome-wide association studies included, involving IOP-lowering drug pharmacogenetics are going to be considered for this review. Abstracts and full published reports will be examined to create a comprehensive list of all current genetic markers being explored in the literature. To avoid information bias, we will include all studies with a valid genotyping methodology and results by triplicate. Also, to prevent selection bias, all studies must follow current glaucoma treatment guidelines endorsed by the American Academy of Ophthalmology and have a full description of their cases and controls.

Condition or domain being studied

Glaucoma is a neurodegenerative disease mainly characterized by the gradual, progressive degeneration of retinal ganglion cells (Fechtner & Weinreb, 1994). Phenotypically there are two distinct entities: primary open angle glaucoma (POAG) (which represents 74% of all cases) and primary angle-closure glaucoma (PACG). Both are manifested initially with a decline in the visual field and, ultimately, irreversible blindness if left untreated. Open-angle glaucoma, however, is an optic neuropathy that might occur with or without an increase in intraocular pressure (IOP), perhaps it may be due to increasing aqueous production and decreased outflow. Angle-closure glaucoma, on the other hand, is identified by a narrowing or closure of the anterior chamber angle leading to inadequate drainage and subsequently elevated IOP (Weinreb &; Khaw, 2004). Given the high prevalence of POAG, this review will focus in this phenotype. 

Regardless of the underlying pathophysiology of glaucomatous neurodegeneration the level of intraocular pressure is undoubtedly associated with both retinal cell and optic nerve fibers damage. Moreover, robust evidence suggests that IOP-lowering drugs might decrease the visual impairment irrespective of the IOP status (Anderson, Drance, & Schulzer, 1998). Current treatment modalities are mainly oriented towards reducing the IOP; these include muscarinic cholinergic agonists, carbonic anhydrase inhibitors, ß-adrenergic receptor (AR) antagonists, α2- AR agonists, and prostaglandin F receptor agonists (Maier et al., 2005). Other factors such as local ischemia-hypoxia (Kaur, Foulds, & Ling, 2008) or excessive stimulation of the glutamatergic system (Vorwerk, Gorla, & Dreyer, 1999) can contribute to ganglion cell death. However, most of these are not subjects of intervention or have not been well studied. Consequently, they will be not considered in this paper.

Participants/population

Cases, in included studies for review, must be defined according to the American Academy of Ophthalmology (AAO) of preferred practice pattern guidelines (Prum et al., 2016). In general, cases must have evidence of at least any optic disc or retinal nerve fiber layer abnormalities, or a reproducible visual field abnormality with an open anterior chamber angle. Any IOP-lowering treatment modality will be considered only if prescribed as monotherapy exceeding four weeks with documented response to treatment. For both cases and controls, there should be no history of ocular surgery, including laser. Also, all studies must explicitly exclude familial cases of glaucoma in their analysis.

Intervention(s), exposure(s)

We will include observational studies that determine genotype based on validated genotyping instruments and all results are corroborated by triplicate. Treated glaucoma cases, for all IOP-lowering drugs, should follow dosage and frequency recommendations from AAO and must be at least administered for four uninterrupted weeks. Response to treatment must be determined by a certified experience ophthalmologist blinded to the genotype status of each participant with appropriate validated instruments by the AAO.

Comparator(s)/control

All observational studies involving IOP-lowering drug pharmacogenetics are going to be considered for this review. For both cases and controls, there should be no history of ocular surgery, including laser. Also, all studies must explicitly exclude familial cases of glaucoma in their analysis.

Context

Main outcome(s)

The main outcome is treatment response to IOP-lowering drugs. For studies before 1996 mean intraocular pressure and standard deviations will be considered for determining treatment response. For current published literature a percent IOP reduction (%ΔIOP) will be seen as an index of response.

Additional outcome(s)

Enlisting associated pharmacogenetic traits will be a secondary outcome of this systematic review.

Data extraction (selection and coding)

Risk of bias (quality) assessment

Bias will be assessed based on the updated Cochrane Back Review Group criteria. As this protocol concerns genetic epidemiology selection bias regarding phenotype or genotype information will include whether cases have been appropriately diagnosed, or even excluding familial cases of glaucoma. Also, regarding information bias, all studies must prove results by triplicate. Bias will be independently assessed by two reviewers, in the event of disagreement a third expert reviewer will be consulted.

Strategy for data synthesis

If possible, relatively homogenous results (I² less than 75%) will be combined and analyzed through meta-analysis. Forest plots will be drafted to evidence the individual effect of each genetic biomarker on glaucoma treatment response. A clinical success as previously stated might depend on the year of publication. Studies before 1996 a mean decrease in IOP will be considered as a response, for posterior manuscripts at least a 30%ΔIOP. The quality of each study will be assessed according to the guidelines for reporting genetic biomarkers adapted for this study (Altman, McShane, Sauerbrei, & Taube, 2012) and the STREGA recommendations (Little et al., 2009).

Analysis of subgroups or subsets

Clinical diversity can be encountered if some observational studies differ in setting, participants (especially different races/ethnicities with differential genome pattern), or even outcome measure (ascertainment of the response with several available validated commercial ophthalmological instruments). The above might lead to statistical heterogeneity increased in this type of genetic association studies by conflicting evidence among subsets of the population. To assess heterogeneity a χ² test at the 0.05 level of significance will be used. I² values greater 

than 75% will be considered highly heterogeneous, between 25-75% moderately and less than 25% comparable. Highly heterogeneous studies will be analyzed using a random-effects model, the rest with a fixed-effect model.

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January 2018
2 Reads

Effects of (-)-epicatechin on frontal cortex DAPC and dysbindin of the mdx mice.

Neurosci Lett 2017 Sep;658:142-149

School of Medicine, University of California San Diego, La Jolla, CA, USA; Seccion de Estudios de Posgrado e Investigacion, Escuela Superior de Medicina, Instituto Politecnico Nacional, Mexico. Electronic address:

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http://dx.doi.org/10.1016/j.neulet.2017.08.056DOI Listing
September 2017
13 Reads
2.055 Impact Factor

[Necrotizing fasciitis caused by cutaneous mucormycosis. A case report].

Cir Cir 2012 Sep-Oct;80(5):462-5

Escuela de Medicina Universidad Panamericana, D.F. México.

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July 2013
5 Reads
0.322 Impact Factor