No association between genetic ancestry and exome sequencing-based diagnosis of inborn errors of metabolism.

J Najera, Y Mavura, A Adhikari, M Kvale, R C Gallagher, N Risch

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Article in NPJ genomic medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

6 authors.

J NajeraInstitute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA. James.Najera@ucsf.edu.

Y MavuraInstitute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA.

A AdhikariIllumina Corporation, San Diego, CA, USA.

M KvaleInstitute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA.

R C GallagherDepartment of Pediatrics, University of California, San Francisco, San Francisco, CA, USA.

N RischInstitute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Inborn errors of metabolism (IEMs) are severe genetic disorders caused by disruptions in metabolic pathways, frequently presenting in early life. Exome (ES) and genome (GS) sequencing have revolutionized the diagnostic approach for Mendelian disorders. However, most studies evaluating the diagnostic yield of ES have focused on predominantly European ancestry populations, leaving significant gaps in understanding its efficacy across diverse ancestries. We evaluated the diagnostic yield of ES in a cohort of 845 newborns with clinically diagnosed IEMs through the California Department of Public Health's Genetic Disease Screening Program (GDSP) and its relationship to genetic ancestry. Over 55% of this ancestrally diverse cohort was maternally reported as non-white/European. By estimating genetic ancestry from exome sequencing data, we assessed its relationship with ES diagnostic outcomes. Diagnostic yield by ES did not significantly differ by any genetic ancestry, supporting its equitable performance across all ancestries among these largely recessive disorders. Higher consanguinity coefficients were associated with increased homozygosity among exome-positive cases, without affecting diagnostic yield across genetic ancestries.

Identifiers

PMID41888158

DOI10.1038/s41525-026-00562-3

PMCPMC13187471

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