Evidence map›Paper›PMID 38124397›Full record

ArticleMolecular biology and evolution2024

Methods for Estimating Personal Disease Risk and Phylogenetic Diversity of Hematopoietic Stem Cells.

Jack M Craig, Glenn S Gerhard, Sudip Sharma, Anastasia Yankovskiy, Sayaka Miura, Sudhir Kumar

Open access · goldAbstract read
In one paragraph

Article in Molecular biology and evolution, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 30% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Jack M CraigInstitute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, USA.ORCID 0000-0003-0590-5944
Glenn S GerhardDepartment of Medical Genetics and Molecular Biochemistry, Lewis Katz School of Medicine, Temple University, Philadelphia, PA, USA.
Sudip SharmaInstitute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, USA.
Anastasia YankovskiyInstitute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, USA.
Sayaka MiuraInstitute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, USA.ORCID 0000-0001-9881-2848
Sudhir KumarInstitute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, USA.ORCID 0000-0002-9918-8212
Temple University · US

Funding

Bioinformatics of metastatic migration historiesR01LM013385 · NLM · TEMPLE UNIV OF THE COMMONWEALTH · PI KUMAR, SUDHIR · 2020 to 2023
$1.4M
Cellular Phylogenetics and EvolutionR01LM014005 · NLM · TEMPLE UNIV OF THE COMMONWEALTH · PI MIURA, SAYAKA · 2022 to 2024
$1.0M
NIH HHS LM013385-04NLM NIH HHS R01 LM013385NLM NIH HHS R01 LM014005
6 · The paper itself

Abstract

An individual's chronological age does not always correspond to the health of different tissues in their body, especially in cases of disease. Therefore, estimating and contrasting the physiological age of tissues with an individual's chronological age may be a useful tool to diagnose disease and its progression. In this study, we present novel metrics to quantify the loss of phylogenetic diversity in hematopoietic stem cells (HSCs), which are precursors to most blood cell types and are associated with many blood-related diseases. These metrics showed an excellent correspondence with an age-related increase in blood cancer incidence, enabling a model to estimate the phylogeny-derived age (phyloAge) of HSCs present in an individual. The HSC phyloAge was generally older than the chronological age of patients suffering from myeloproliferative neoplasms (MPNs). We present a model that relates excess HSC aging with increased MPN risk. It predicted an over 200 times greater risk based on the HSC phylogenies of the youngest MPN patients analyzed. Our new metrics are designed to be robust to sampling biases and do not rely on prior knowledge of driver mutations or physiological assessments. Consequently, they complement conventional biomarker-based methods to estimate physiological age and disease risk.

Indexed as

Myeloproliferative DisordersNeoplasmsAgingHematopoietic Stem CellsHumansPhylogenybiological agecancer riskhematopoietic stem cellssomatic mutations

Identifiers

PMID38124397
PMCPMC10768883
OpenAlexW4390061454

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.