National Health and Nutrition Examination Survey (NHANES), 1999-2000

Tiro, Jasmin A.; Lee, Simon J. Craddock; Lipshultz, Steven E.; Miller, Tracie L.; Wilkinson, James D.; Mestre, Miriam A.; Miller, Donna L.; Fernandez, Cristina A.; Lee, Dong Hoon; Hall, Martica H.; Young-Hyman, Deborah Lee; Bustillo, Natalie E.; Pellowski, Jennifer; Bryant, Vaughn; Frankel, Anne; Khanfer, Riyad; Felleman, Benjamin I.; Marlatt, G. Alan; Tookes, Hansel; Stringer, Deborah M.; Denollet, Johan; Hawkley, Louise C.; Arlt, Wiebke; Vitlić, Ana; Toescu, Emil C.; Chiba-Falek, Ornit; Beaton, Elliott A.; Gatchel, Robert J.; Knauf, Matthew T.; Couck, Marijke; Hoffman, Richard M.; Gidron, Yori; Sharma, Leigh A.; Dorsey, Susan M.; Nakajima, Motohiro; Al’Absi, Mustafa; Rose, Jed E.; Haney, Alyssa; Okun, Michele L.; Aldred, Sarah; Flaten, Magne Arve; Turner, J. Rick; Insana, Salvatore; Galik, Elizabeth; Segal, Sydney; Barrett, Chad; Whang, William; Harnack, Lisa; Gambert, Steven

doi:10.3886/icpsr25501.v3

Cited by 3 publications

(1 citation statement)

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“…We briefly summarize the results of five studies which predicted chronological age using laboratory biomarkers (1)(2)(3)(4)(5). Three papers leveraged the NHANES [18][19][20][21][22][23][24][25] dataset to predict chronological age as a function of biochemical and blood count biomarkers 6,7,26 The diversity of the biomarkers covered by these models means that they should be compared to our models with caution; however, they still provide orders of magnitude for the prediction accuracy that can be reached when leveraging laboratory values to predict chronological age.…”

Section: Laboratory Biomarkersmentioning

confidence: 99%

Comparing the genetic and environmental architecture of blood count, blood biochemistry and urine biochemistry biological ages with machine learning

Diai

Thouvenot

et al. 2021

Preprint

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While a large number of biological age predictors have been built from blood samples, a blood count-based biological age predictor is lacking, and the genetic and environmental factors associated with blood-measured accelerated aging remain elusive. In the following, we leveraged 31 blood count biomarkers measured from 489,079 blood samples, 28 blood biochemistry biomarkers measured from 245,147 blood samples, and four urine biochemistry biomarkers measured from 158,381 samples to build three distinct biological age predictors by training machine learning models to predict age. Blood biochemistry significantly outperformed blood count and urine biochemistry in terms of age prediction (RMSE: 5.92+-0.02 vs. 7.60+-0.02 years and 7.72+-0.04 years). We performed genome wide association studies [GWASs], and found accelerated blood biochemistry, blood count and urine biochemistry aging to be respectively 26.2+-0.3%, 18.1+-0.2% and 10.5+-0.5% GWAS-heritable. We identified 1,081 single nucleotide polymorphisms [SNPs] associated with accelerated blood biochemistry aging, 2,636 SNPs associated with accelerated blood cells aging and 24 SNPs associated with accelerated urine biochemistry aging. Similarly, we identified biomarkers, clinical phenotypes, diseases, environmental and socioeconomic factors associated with accelerated blood biochemistry, blood cells and urine biochemistry aging.

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Section: Laboratory Biomarkersmentioning

confidence: 99%

Comparing the genetic and environmental architecture of blood count, blood biochemistry and urine biochemistry biological ages with machine learning

Diai

Thouvenot

et al. 2021

Preprint

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The NYCKidSeq project: study protocol for a randomized controlled trial incorporating genomics into the clinical care of diverse New York City children

Odgis

Gallagher

Suckiel

et al. 2021

Trials

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Background Increasingly, genomics is informing clinical practice, but challenges remain for medical professionals lacking genetics expertise, and in access to and clinical utility of genomic testing for minority and underrepresented populations. The latter is a particularly pernicious problem due to the historical lack of inclusion of racially and ethnically diverse populations in genomic research and genomic medicine. A further challenge is the rapidly changing landscape of genetic tests and considerations of cost, interpretation, and diagnostic yield for emerging modalities like whole-genome sequencing. Methods The NYCKidSeq project is a randomized controlled trial recruiting 1130 children and young adults predominantly from Harlem and the Bronx with suspected genetic disorders in three disease categories: neurologic, cardiovascular, and immunologic. Two clinical genetic tests will be performed for each participant, either proband, duo, or trio whole-genome sequencing (depending on sample availability) and proband targeted gene panels. Clinical utility, cost, and diagnostic yield of both testing modalities will be assessed. This study will evaluate the use of a novel, digital platform (GUÍA) to digitize the return of genomic results experience and improve participant understanding for English- and Spanish-speaking families. Surveys will collect data at three study visits: baseline (0 months), result disclosure visit (ROR1, + 3 months), and follow-up visit (ROR2, + 9 months). Outcomes will assess parental understanding of and attitudes toward receiving genomic results for their child and behavioral, psychological, and social impact of results. We will also conduct a pilot study to assess a digital tool called GenomeDiver designed to enhance communication between clinicians and genetic testing labs. We will evaluate GenomeDiver’s ability to increase the diagnostic yield compared to standard practices, improve clinician’s ability to perform targeted reverse phenotyping, and increase the efficiency of genetic testing lab personnel. Discussion The NYCKidSeq project will contribute to the innovations and best practices in communicating genomic test results to diverse populations. This work will inform strategies for implementing genomic medicine in health systems serving diverse populations using methods that are clinically useful, technologically savvy, culturally sensitive, and ethically sound. Trial registration ClinicalTrials.govNCT03738098. Registered on November 13, 2018 Trial Sponsor: Icahn School of Medicine at Mount Sinai Contact Name: Eimear Kenny, PhD (Principal Investigator) Address: Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Pl., Box 1003, New York, NY 10029 Email: eimear.kenny@mssm.edu

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The TeleKidSeq pilot study: incorporating telehealth into clinical care of children from diverse backgrounds undergoing whole genome sequencing

Sebastin

Odgis

Suckiel

et al. 2023

Pilot Feasibility Stud

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Background The COVID-19 pandemic forced healthcare institutions and many clinical research programs to adopt telehealth modalities in order to mitigate viral spread. With the expanded use of telehealth, there is the potential to increase access to genomic medicine to medically underserved populations, yet little is known about how best to communicate genomic results via telehealth while also ensuring equitable access. NYCKidSeq, a multi-institutional clinical genomics research program in New York City, launched the TeleKidSeq pilot study to assess alternative forms of genomic communication and telehealth service delivery models with families from medically underserved populations. Methods We aim to enroll 496 participants between 0 and 21 years old to receive clinical genome sequencing. These individuals have a neurologic, cardiovascular, and/or immunologic disease. Participants will be English- or Spanish-speaking and predominantly from underrepresented groups who receive care in the New York metropolitan area. Prior to enrollment, participants will be randomized to either genetic counseling via videoconferencing with screen-sharing or genetic counseling via videoconferencing without screen-sharing. Using surveys administered at baseline, results disclosure, and 6-months post-results disclosure, we will evaluate the impact of the use of screen-sharing on participant understanding, satisfaction, and uptake of medical recommendations, as well as the psychological and socioeconomic implications of obtaining genome sequencing. Clinical utility, cost, and diagnostic yield of genome sequencing will also be assessed. Discussion The TeleKidSeq pilot study will contribute to innovations in communicating genomic test results to diverse populations through telehealth technology. In conjunction with NYCKidSeq, this work will inform best practices for the implementation of genomic medicine in diverse, English- and Spanish-speaking populations.

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National Health and Nutrition Examination Survey (NHANES), 1999-2000

Cited by 3 publications

References 0 publications

Comparing the genetic and environmental architecture of blood count, blood biochemistry and urine biochemistry biological ages with machine learning

Comparing the genetic and environmental architecture of blood count, blood biochemistry and urine biochemistry biological ages with machine learning

The NYCKidSeq project: study protocol for a randomized controlled trial incorporating genomics into the clinical care of diverse New York City children

The TeleKidSeq pilot study: incorporating telehealth into clinical care of children from diverse backgrounds undergoing whole genome sequencing

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