The impact of clinical genome sequencing in a global population with suspected rare genetic disease

Abstract

There is mounting evidence of the value of clinical genome sequencing (cGS) in individuals with suspected rare genetic disease (RGD), but cGS performance and impact on clinical care in a diverse population drawn from both high-income countries (HICs) and low- and middle-income countries (LMICs) has not been investigated. The iHope program, a philanthropic cGS initiative, established a network of 24 clinical sites in eight countries through which it provided cGS to individuals with signs or symptoms of an RGD and constrained access to molecular testing. A total of 1,004 individuals (median age, 6.5 years; 53.5% male) with diverse ancestral backgrounds (51.8% non-majority European) were assessed from June 2016 to September 2021. The diagnostic yield of cGS was 41.4% (416/1,004), with individuals from LMIC sites 1.7 times more likely to receive a positive test result compared to HIC sites (LMIC 56.5% [195/345] vs. HIC 33.5% [221/659], OR 2.6, 95% CI 1.9-3.4, p < 0.0001). A change in diagnostic evaluation occurred in 76.9% (514/668) of individuals. Change of management, inclusive of specialty referrals, imaging and testing, therapeutic interventions, and palliative care, was reported in 41.4% (285/694) of individuals, which increased to 69.2% (480/694) when genetic counseling and avoidance of additional testing were also included. Individuals from LMIC sites were as likely as their HIC counterparts to experience a change in diagnostic evaluation (OR 6.1, 95% CI 1.1-∞, p = 0.05) and change of management (OR 0.9, 95% CI 0.5-1.3, p = 0.49). Increased access to genomic testing may support diagnostic equity and the reduction of global health care disparities.

Keywords: change of management; clinical genome testing; clinical utility; diagnostic equity; genetic testing; low- and middle-income; rare disease; rare genetic disease; whole-genome sequencing.

Figure 1

STROBE diagram iHope program observational cohort ascertainment and cGS impact survey responses depicted using a STROBE diagram. Abbreviations: cGS, clinical genome sequencing; HIC, high-income country; LMIC, low- and middle-income country.

Figure 2

Demographics and phenotypic presentation of the iHope cohort (A) Principal component analysis of the iHope cohort individuals (black) overlayed on seven human superpopulations derived from the 1000 Genomes, Human Genome Diversity, and Simons Genome Diversity datasets. (B) Age and sex distributions stratified by high-income country (HIC) and low- and middle-income country (LMIC) sites. HIC age (y): mean 8.9, median 6.3, range 0 days–77.1 years; LMIC age (y): mean 9.6, median 6.6, range 26 days–77.9 years with two males of unknown age assigned the mean age for individuals from LMIC sites. HIC sex: male 350/659 (53.1%), female 309/659 (46.8%); LMIC sex: male 187/345 (54.2%), female 158/345 (45.7%). There are no statistically significant differences in age and sex distributions between the HIC and LMIC populations (p = 0.36 and p = 0.69). (C) Summary distribution of top-level Human Phenotype Ontology terms nested beneath “Phenotypic abnormality” (HP:0000118) across the iHope cohort and stratified by HIC and LMIC.

Figure 3

Diagnostic yield of cGS and its impact on clinical diagnosis and diagnostic evaluation (A) Overall diagnostic yield of cGS stratified by test result category and by HIC and LMIC. (B) Change in clinical diagnosis due to cGS grouped by HIC and LMIC sites. Survey response options included “yes,” “no,” and “not applicable.” Survey responses endorsing a change in clinical diagnosis are stratified by test result category. (C) The impact of cGS results on diagnostic evaluation. Response options are reflected in the text in the lower left, with black rectangles representing endorsement by the responding clinician. Multiple response options could be endorsed. The vertical black lines connecting black rectangles indicate a response combination. Bar plots above each set of responses indicate the proportion of individuals with a DE response combination stratified by test result category. Stacked bars to the far right reflect the combined total responses supportive of an impact on diagnostic evaluation.

Figure 4

Changes of management associated with cGS testing results (A) Change of management (COM) across the cohort and stratified by HIC and LMIC sites and test result category. Response options are reflected in the text in the lower left, with black squares representing endorsement of a COM category. Multiple response options could be endorsed. The vertical black lines connecting black rectangles reflect a combination of endorsed responses. Bar plots above each set of responses indicate the proportion of individuals with the indicated COM response combination stratified by test result category. (B) Distribution of COM categorized to the referrals, imaging and testing COM category, stratified by HIC and LMIC sites and test result category. (C) Distributions of COM categorized to the therapeutics COM category, stratified by HIC and LMIC sites and test result category.