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. 2024 Oct 28;9(1):51.
doi: 10.1038/s41525-024-00434-8.

Clinical genome sequencing in patients with suspected rare genetic disease in Peru

Jeny Bazalar-Montoya #  1   2 , Mario Cornejo-Olivas #  3   4 , Milagros M Duenas-Roque #  5 , Nelson Purizaca-Rosillo  5 , Richard S Rodriguez  2   4 , Karina Milla-Neyra  4 , Carlos A De La Torre-Hernandez  5 , Elison Sarapura-Castro  3   4 , Carolina I Galarreta Aima  6 , Gioconda Manassero-Morales  1 , Giulliana Chávez-Pasco  1 , Luis Celis-García  1 , Jorge E La Serna-Infantes  4   7 ; Illumina Laboratory Services Bioinformatics, Software, Interpretation and Customer Support; Evgenii Chekalin  8 , Erin Thorpe  8   9 , Ryan J Taft  10   11
Collaborators, Affiliations

Clinical genome sequencing in patients with suspected rare genetic disease in Peru

Jeny Bazalar-Montoya et al. NPJ Genom Med. .

Abstract

There is limited access to molecular genetic testing in most low- and middle-income countries. The iHope program provides clinical genome sequencing (cGS) to underserved individuals with signs or symptoms of rare genetic diseases and limited or no access to molecular genetic testing. Here we describe the performance and impact of cGS in 247 patients from three clinics in Peru. Although most patients had at least one genetic test prior to cGS (70.9%), the most frequent was karyotyping (53.4%). The diagnostic yield of cGS was 54.3%, with candidate variants reported in an additional 22.3% of patients. Clinical GS results impacted clinician diagnostic evaluation in 85.0% and genetic counseling in 72.1% of cases. Changes in management were reported in 71.3%, inclusive of referrals (64.7%), therapeutics (26.3%), laboratory or physiological testing (25.5%), imaging (19%), and palliative care (17.4%), suggesting that increased availability of genomic testing in Peru would enable improved patient management.

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Conflict of interest statement

Ryan J. Taft, Erin Thorpe, Subramanian S. Ajay, James Avecilla, Krista Bluske, Carolyn M. Brown, Amanda Buchanan, Brendan Burns, Nicole Burns, Anjana Chandrasekhar, Amanda Clause, Katie Golden-Grant, R. Tanner Hagelstrom, Rueben Hejja, Basil Juan, Alka Malhotra, Philip Medrano, Becky Milewski, Felipe Mullen, Viswateja Nelakuditi, Vani Rajan, Revathi Rajkumar, Samin Sajan, Zinayida Schlachetzki, Sarah Schmidt, Julie Taylor, and Brittany Thomas, Evgenii Chekalin, Max Arseneault, Maren Bennett, Aditi Chawla, Alison J. Coffey, Akanchha Kesari, Denise L. Perry, Ajay Ramakrishnan Sylwia Urbaniak, Andrew Warren were employees of and stockholders in Illumina, Inc. during this study.

Figures

Fig. 1
Fig. 1. Geographic distribution of iHope patients in Peru.
The distribution of patients participating in the iHope program is shown across Peru. Participating individuals are shown as purple circles, with the size of the circle denoting the number of patients from a given ZIP code. More than a third of patients (37%) were drawn from the capital city, Lima, which is shown in the inset in the lower left. Geographic barriers potentially impacting patient accessibility to clinical sites in Lima include both the Andes mountains (shown as the high-elevation band in dark brown) and the Amazon rainforest (shown in dark green). The cartographic and geographic data used to generate this figure were drawn from GPL3-licensed sources, as detailed in the “Statistical analysis” section.
Fig. 2
Fig. 2. Patient selection and prior genetic testing.
a The total proportion of patients, and the proportion from each site, that were associated with each of iHope program selection criteria. Patients could be associated with more than one selection criteria. Broad differential diagnosis was the most common rationale for program inclusion. b The proportion of iHope patients with genetic testing prior to cGS stratified by site and type of genetic test. WES: whole exome sequencing; HNERM Hospital Nacional Edgardo Rebagliati Martins, INCN Instituto Nacional de Ciencias Neurológicas, INSNSB Instituto Nacional de Salud Niño-San Borja.
Fig. 3
Fig. 3. Patient phenotypes.
Summary distribution of top-level Human Phenotype Ontology terms nested beneath “Phenotypic abnormality” (HP:0000118) across the iHope cohort and grouped by clinical site. Patient phenotypes were diverse and complex, and with abnormalities of the nervous system, skeletal system, and head or neck, the most frequently identified Human Phenotype Ontology root ancestor terms overall and for each site. Differences in observed HPO root ancestor terms by site are detailed in Supplementary Table 2. HNERM Hospital Nacional Edgardo Rebagliati Martins, INCN Instituto Nacional de Ciencias Neurológicas, INSNSB Instituto Nacional de Salud Niño-San Borja.
Fig. 4
Fig. 4. Diagnostic yield and reported variants.
a Outcomes of cGS stratified by test result category and by clinical site. b Distribution of variant types reported across the iHope cohort and grouped by site. SNV single nucleotide variant; Indel: insertion or deletion, CNV copy number variant, STR short tandem repeat variant, MT SNV single nucleotide variant in the mitochondrial genome, SMA c.840 C allele in the SMN1 gene not detected, UPD uniparental disomy, HNERM Hospital Nacional Edgardo Rebagliati Martins, INCN Instituto Nacional de Ciencias Neurológicas, INSNSB Instituto Nacional de Salud Niño-San Borja.
Fig. 5
Fig. 5. Impact on the diagnostic evaluation (DE), change in management (COM), and genetic counseling (GC).
a The impact of cGS results on the diagnostic evaluation, b change of management, and c genetic counseling. For each, multiple response options could be endorsed for a single patient. Results are displayed for the cohort overall and by site. HNERM Hospital Nacional Edgardo Rebagliati Martins, INCN Instituto Nacional de Ciencias Neurológicas, INSNSB Instituto Nacional de Salud Niño-San Borja.
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