Evidence map›Paper›PMID 42100348›Full record

ReviewFrontiers in genetics2026

Decoding thalassemia and sickle cell disease: advances in molecular technologies for comprehensive variant detection.

Emelie Foord, Darius Sairafi, Monika Berg, Sofia Westerling, Toheeb Adigun, Mehmet Uzunel, Thessalia Papasavva, Michael Uhlin

Abstract readReview
In one paragraph

Review in Frontiers in genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Emelie FoordDepartment of Medicine, Karolinska Institutet, Huddinge, Sweden.
Darius SairafiDevyser AB, Stockholm, Sweden.
Monika BergDevyser AB, Stockholm, Sweden.
Sofia WesterlingDevyser AB, Stockholm, Sweden.
Toheeb AdigunDevyser AB, Stockholm, Sweden.
Mehmet UzunelDevyser AB, Stockholm, Sweden.
Thessalia PapasavvaBlood Disorder Genetics and Thalassaemia, The Cyprus Institute of Neurology and Genetics (CING), Nicosia, Cyprus.
Michael UhlinDepartment of Medicine, Karolinska Institutet, Huddinge, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Thalassemia and sickle cell disease are inherited hemoglobinopathies caused by pathogenic variants in the globin genes and represent a major global health burden. Despite major advances in screening and diagnostics, challenges persist due to extensive genetic heterogeneity and complex genotype-phenotype relationships. Conventional workflows typically combine hematologic and biochemical analyses with targeted DNA-based testing. However, traditional molecular approaches are often sequential and labor-intensive, with limited capacity to detect the full spectrum of pathogenic variation. Advances in next-generation sequencing (NGS) now enables integrated and comprehensive strategies to support hemoglobinopathy diagnostics and screening follow-up. Currently available NGS-based platforms allow simultaneous detection of diverse variant classes, including sequence variants and copy number alterations, across multiple disease-relevant genes, including genetic modifiers that may influence disease severity. This review summarizes the genetic basis of thalassemia and sickle cell disease and compiles traditional and emerging molecular testing methodologies. It further discusses the strengths, limitations and utility of NGS-based platforms, and considers their role in shaping future screening and diagnostic workflows for hemoglobinopathies.

Indexed as

hemoglobinopathiesmolecular diagnosticsnext-generation sequencing (NGS)screening follow-upsickle cell diseasethalassemia

Identifiers

PMID42100348
PMCPMC13148797

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Registered trials

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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.