Phenome-wide Mendelian randomization mapping the influence of the plasma proteome on complex diseases

Abstract

The human proteome is a major source of therapeutic targets. Recent genetic association analyses of the plasma proteome enable systematic evaluation of the causal consequences of variation in plasma protein levels. Here we estimated the effects of 1,002 proteins on 225 phenotypes using two-sample Mendelian randomization (MR) and colocalization. Of 413 associations supported by evidence from MR, 130 (31.5%) were not supported by results of colocalization analyses, suggesting that genetic confounding due to linkage disequilibrium (LD) is widespread in naïve phenome-wide association studies of proteins. Combining MR and colocalization evidence in cis-only analyses, we identified 111 putatively causal effects between 65 proteins and 52 disease-related phenotypes ( www.epigraphdb.org/pqtl/ ). Evaluation of data from historic drug development programs showed that target-indication pairs with MR and colocalization support were more likely to be approved, evidencing the value of this approach in identifying and prioritizing potential therapeutic targets.

Identifying drug targets for neurological and psychiatric disease via genetics and the brain transcriptome

“…For example, two sample MR studies have systematically explored causal relationships between the transcriptome [8,9,10]. methylome [11] and proteome [12] and complex traits. Zhu et al performed MR between blood eQTLs and five complex traits and found potential causal effects for 126 genes in total, including 25 novel genes previously unreported in the literature [9].…”

“…Zhu et al performed MR between blood eQTLs and five complex traits and found potential causal effects for 126 genes in total, including 25 novel genes previously unreported in the literature [9]. Richardson et al [11] and Zheng et al [12] performed MR on a wider phenome-wide scale and found putative causal effects for 1,148 methylation quantitative trait loci (mQTLs) on 139 complex traits and 111 protein quantitative trait loci (pQTLs) on 225 complex traits respectively. After causal variants have been identified, a follow up MR phenome-wide association analysis [13] can then be conducted to assess a gene's suitability as a drug target.…”

A Neanderthal OAS1 isoform Protects Against COVID-19 Susceptibility and Severity: Results from Mendelian Randomization and Case-Control Studies

“…Recent advances in large-scale proteomics have enabled the measurement of thousands of circulating proteins at once and when combined with evidence from human genetics, such targets greatly improve the probability of drug development success. [6][7][8] While de novo drug development will take time-even in the accelerated arena of COVID-19 therapiesrepositioning of currently available molecules targeting those proteins, if they exist, could also provide an accelerated opportunity to deliver new therapies to patients.…”

“…We selectedproteins with only cis-pQTLs to test their effects on COVID-19 outcomes, because they are less likely to be affected by potential horizontal pleiotropy. The cis-pQTLs were defined as the genome-wide significant SNPs (P < 5 × 10 −8 ) with the lowest P value within 1 Mb of the transcription start site (TSS) of the gene encoding the measured protein 8. We selected one cis-pQTL per protein per each study.…”

Pairwise genetic interactions modulate lipid plasma levels and cellular uptake

“…Genetic support for a drug target increases the probability that a medicine directed against the respective target will succeed by several fold 11,12 . We thus hypothesized that genetics might also assist in nominating drug target pairs that, when addressed jointly, will have a higher probability to reach a desired therapeutic benefit.…”