The phenotype-genotype reference map: Improving biobank data science through replication.

Population-scale biobanks linked to electronic health record data provide vast opportunities to extend our knowledge of human genetics and discover new phenotype-genotype associations. Given their dense phenotype data, biobanks can also facilitate replication studies on a phenome-wide scale. Here, we introduce the phenotype-genotype reference map (PGRM), a set of 5,879 genetic associations from 523 GWAS publications that can be used for high-throughput replication experiments. PGRM phenotypes are standardized as phecodes, ensuring interoperability between biobanks. We applied the PGRM to five ancestry-specific cohorts from four independent biobanks and found evidence of robust replications across a wide array of phenotypes. We show how the PGRM can be used to detect data corruption and to empirically assess parameters for phenome-wide studies. Finally, we use the PGRM to explore factors associated with replicability of GWAS results.

Genetic Associations of Persistent Opioid Use After Surgery Point to OPRM1 but Not Other Opioid-Related Loci as the Main Driver of Opioid Use Disorder.

Persistent opioid use after surgery is a common morbidity outcome associated with subsequent opioid use disorder, overdose, and death. While phenotypic associations have been described, genetic associations remain unidentified. Here, we conducted the largest genetic study of persistent opioid use after surgery, comprising ~40,000 non-Hispanic, European-ancestry Michigan Genomics Initiative participants (3198 cases and 36,321 surgically exposed controls). Our study primarily focused on the reproducibility and reliability of 72 genetic studies of opioid use disorder phenotypes. Nominal associations (p < 0.05) occurred at 12 of 80 unique (r2 < 0.8) signals from these studies. Six occurred in OPRM1 (most significant: rs79704991-T, OR = 1.17, p = 8.7 × 10-5), with two surviving multiple testing correction. Other associations were rs640561-LRRIQ3 (p = 0.015), rs4680-COMT (p = 0.016), rs9478495 (p = 0.017, intergenic), rs10886472-GRK5 (p = 0.028), rs9291211-SLC30A9/BEND4 (p = 0.043), and rs112068658-KCNN1 (p = 0.048). Two highly referenced genes, OPRD1 and DRD2/ANKK1, had no signals in MGI. Associations at previously identified OPRM1 variants suggest common biology between persistent opioid use and opioid use disorder, further demonstrating connections between opioid dependence and addiction phenotypes. Lack of significant associations at other variants challenges previous studies' reliability.

Genes for Good: Engaging the Public in Genetics Research via Social Media.

The Genes for Good study uses social media to engage a large, diverse participant pool in genetics research and education. Health history and daily tracking surveys are administered through a Facebook application, and participants who complete a minimum number of surveys are mailed a saliva sample kit ("spit kit") to collect DNA for genotyping. As of March 2019, we engaged >80,000 individuals, sent spit kits to >32,000 individuals who met minimum participation requirements, and collected >27,000 spit kits. Participants come from all 50 states and include a diversity of ancestral backgrounds. Rates of important chronic health indicators are consistent with those estimated for the general U.S. population using more traditional study designs. However, our sample is younger and contains a greater percentage of females than the general population. As one means of verifying data quality, we have replicated genome-wide association studies (GWASs) for exemplar traits, such as asthma, diabetes, body mass index (BMI), and pigmentation. The flexible framework of the web application makes it relatively simple to add new questionnaires and for other researchers to collaborate. We anticipate that the study sample will continue to grow and that future analyses may further capitalize on the strengths of the longitudinal data in combination with genetic information.