Whole genome sequencing in the Middle Eastern Qatari population identifies genetic associations with 45 clinically relevant traits

Abstract

Clinical laboratory tests play a pivotal role in medical decision making, but little is known about their genetic variability between populations. We report a genome-wide association study with 45 clinically relevant traits from the population of Qatar using a whole genome sequencing approach in a discovery set of 6218 individuals and replication in 7768 subjects. Trait heritability is more similar between Qatari and European populations (r = 0.81) than with Africans (r = 0.44). We identify 281 distinct variant-trait-associations at genome wide significance that replicate known associations. Allele frequencies for replicated loci show higher correlations with European (r = 0.94) than with African (r = 0.85) or Japanese (r = 0.80) populations. We find differences in linkage disequilibrium patterns and in effect sizes of the replicated loci compared to previous reports. We also report 17 novel and Qatari-predominate signals providing insights into the biological pathways regulating these traits. We observe that European-derived polygenic scores (PGS) have reduced predictive performance in the Qatari population which could have implications for the translation of PGS between populations and their future application in precision medicine.

Qatar Genome: Insights on Genomics from the Middle East

“…To gain insights into the genetic architecture of health and disease-related quantitative traits, we performed the first genome wide association studies of a list of 45 quantitative traits in 6,045 individuals from the Qatari population (Thareja et al, 2021). Several important findings of this comprehensive study include replication of multiple associations reported in Caucasian and Asian GWASs; uncovering differences in allele frequencies and LD patterns for replicated loci; and discovery of novel genetic associations mostly with variants common in the QGP but rare in other populations.…”

Generalizability of GWA-Identified Genetic Risk Variants for Metabolic Traits to Populations from the Arabian Peninsula

“…In a recent study, Thareja et al [28] performed genome-wide association tests to delineate risk variants for 45 clinically relevant traits using a discovery set of whole-genome sequences of 6218 Qatari individuals. The examined traits included two (namely anthropometry and lipid) of the four classes of metabolic traits examined in our study [4].…”

“…The same trait-variant associations among Qatar and Kuwait is highlighted with bold and italics in list of traits. Thareja et al [28] observed four GWA-identified association signals in the Qatari cohort relating to anthropometric traits at genome-wide significance, which he Qatari cohort relating to lipid traits at genome-wide significance, which included 22 identified in the Kuwaiti meta-analysis cohort [4]; 17 of these 22 associations were with the same exact lipid trait in the Kuwaiti cohort; of the remaining five, four were observed with related lipid traits; and one with a related metabolic trait (FPG).…”

“…The results presented by the above-mentioned two studies [4,28] from Kuwait and Qatar indicate that the assessment of generalizability of GWA-identified association signals in the Arab population is still an "open" question. Though it is possible that the limited sample sizes and differences in study designs may contribute to the observed low extent of transferability, the role of differences in factors such as phenotypic variance due to unique environmental conditions, allele frequencies, and linkage disequilibrium profiles cannot be ruled out.…”

Poking COVID-19: insights on genomic constraints among immune-related genes between Qatari and Italian populations

“…In this cohort, each sample was characterized by a disease severity code. The disease severity classes are defined as follows: 1) Asymptomatic/Paucisymptomatic, 2) Severe, 3) Critical/life-threatening [37]. We used this information to investigate if we could identify any contribution of the singleton burden of the prioritized genes to the classification.…”