A survey of proteomic variation across two ethnic groups in Nigeria and its relationship to obesity risk
bioRxiv (Cold Spring Harbor Laboratory)(2022)
Abstract
Proteomic variation between individuals has immense potential for identifying novel drug targets and disease mechanisms. However, with high-throughput proteomic technologies still in their infancy, they have largely been applied in large majority European ancestry cohorts (e.g. the UK Biobank). An open question is the degree to which proteomic signatures seen in European and other groups mirror those seen in diverse populations, such as cohorts from Africa. Coupled with genetic information, we can also gain a better understanding of the role of genetic variants in the regulation of the proteome and subsequent disease mechanisms.
To address the gap in our understanding of proteomic variation in individuals of African ancestry, we collected proteomic data from 176 individuals across two ethnic groups (Igbo and Yoruba) in Nigeria. These individuals were also stratified into high BMI (BMI > 30 kg/m2) and normal BMI (20 kg/m2 < BMI < 30 kg/m2) categories. We characterized differences in plasma protein abundance using the Olink Explore 1536 panel between high and normal BMI individuals, finding strong associations consistent with previously known signals in individuals of European descent. We additionally found 73 sentinel cis-pQTL in this dataset, with 21 lead cis-pQTL not observed in catalogs of variation from European-ancestry individuals. In summary, our study highlights the value of leveraging proteomic data in cohorts of diverse ancestry for investigating trait-specific mechanisms and discovering novel genetic regulators of the plasma proteome.
### Competing Interest Statement
At the time research was conducted, A.B., K.P.d.A., G.E., C.N., Y.I., O.O., E.J, A.Y., A.E.O., J.P., C.O'D., and P.F. were employed by 54gene, Inc and are beneficiaries of compensation through this employment. Funding for this study was provided by 54gene, Inc.
MoreTranslated text
Key words
proteomic variation,obesity risk,nigeria
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined