Postmortem toxicology findings from the Camden Opioid Research Initiative.

The United States continues to be impacted by decades of an opioid misuse epidemic, worsened by the COVID-19 pandemic and by the growing prevalence of highly potent synthetic opioids (HPSO) such as fentanyl. In instances of a toxicity event, first-response administration of reversal medications such as naloxone can be insufficient to fully counteract the effects of HPSO, particularly when there is co-occurring substance use. In an effort to characterize and study this multi-faceted problem, the Camden Opioid Research Initiative (CORI) has been formed. The CORI study has collected and analyzed post-mortem toxicology data from 42 cases of decedents who expired from opioid-related toxicity in the South New Jersey region to characterize substance use profiles. Co-occurring substance use, whether by intent or through possible contamination of the illicit opioid supply, is pervasive among deaths due to opioid toxicity, and evidence of medication-assisted treatment is scarce. Nearly all (98%) of the toxicology cases show the presence of the HPSO, fentanyl, and very few (7%) results detected evidence of medication-assisted treatment for opioid use disorder, such as buprenorphine or methadone, at the time of death. The opioid toxicity reversal drug, naloxone, was detected in 19% of cases, but 100% of cases expressed one or more stimulants, and sedatives including xylazine were detected in 48% of cases. These results showing complex substance use profiles indicate that efforts at mitigating the opioid misuse epidemic must address the complications presented by co-occurring stimulant and other substance use, and reduce barriers to and stigmas of seeking effective medication-assisted treatments.

Patient Perceptions and Potential Utility of Pharmacogenetic Testing in Chronic Pain Management and Opioid Use Disorder in the Camden Opioid Research Initiative.

Pharmacogenetics (PGx) has the potential to improve opioid medication management. Here, we present patient perception data, pharmacogenetic data and medication management trends in patients with chronic pain (arm 1) and opioid use disorder (arm 2) treated at Cooper University Health Care in Camden City, NJ. Our results demonstrate that the majority of patients in both arms of the study (55% and 65%, respectively) are open to pharmacogenetic testing, and most (66% and 69%, respectively) believe that genetic testing has the potential to improve their medical care. Our results further support the potential for CYP2D6 PGx testing to inform chronic pain medication management for poor metabolizers (PMs) and ultrarapid metabolizers (UMs). Future efforts to implement PGx testing in chronic pain management, however, must address patient concerns about genetic test result access and genetic discrimination.

Pharmacogenomics: From Basic Research to Clinical Implementation.

The established contribution of genetic variation to drug response has the potential to improve drug efficacy and reduce drug toxicity [...].

Common Treatment, Common Variant: Evolutionary Prediction of Functional Pharmacogenomic Variants.

Pharmacogenomics holds the promise of personalized drug efficacy optimization and drug toxicity minimization. Much of the research conducted to date, however, suffers from an ascertainment bias towards European participants. Here, we leverage publicly available, whole genome sequencing data collected from global populations, evolutionary characteristics, and annotated protein features to construct a new in silico machine learning pharmacogenetic identification method called XGB-PGX. When applied to pharmacogenetic data, XGB-PGX outperformed all existing prediction methods and identified over 2000 new pharmacogenetic variants. While there are modest pharmacogenetic allele frequency distribution differences across global population samples, the most striking distinction is between the relatively rare putatively neutral pharmacogene variants and the relatively common established and newly predicted functional pharamacogenetic variants. Our findings therefore support a focus on individual patient pharmacogenetic testing rather than on clinical presumptions about patient race, ethnicity, or ancestral geographic residence. We further encourage more attention be given to the impact of common variation on drug response and propose a new 'common treatment, common variant' perspective for pharmacogenetic prediction that is distinct from the types of variation that underlie complex and Mendelian disease. XGB-PGX has identified many new pharmacovariants that are present across all global communities; however, communities that have been underrepresented in genomic research are likely to benefit the most from XGB-PGX's in silico predictions.

Testing a best practices risk result format to communicate genetic risks.

OBJECTIVE: To investigate the effect of a genetic report format using risk communication "best-practices" on risk perceptions, in part to reduce risk overestimates. METHODS: Adults (N = 470) from the Coriell Personalized Medicine Collaborative (CPMC) were randomized to a 2 × 2 experimental design to receive a hypothetical "personalized" genetic risk result for leukemia (relative risk = 1.5 or 2.5) through either the standard CPMC report (N = 232) or an enriched report informed by best practices (N = 238). A one-time, online survey assessed numeracy and risk perceptions including "feelings of risk" and a numerical estimate. RESULTS: Regardless of numeracy, participants who received the enriched report had fewer overestimates of their lifetime risk estimate (LRE; odds ratio = 0.19, p < .001) and lower feelings of risk on two of three measures (p < .001). Participants with higher numeracy scores had fewer overestimates of LRE (OR = 0.66, p < .001) and lower feelings of risk on two out of three measures (p ≤ .01); the interaction between numeracy and report format was non-significant. CONCLUSION: The enriched report produced more accurate LRE and lower risk perceptions regardless of numeracy level, suggesting the enriched format was helpful to individuals irrespective of numeracy ability. PRACTICE IMPLICATIONS: Best practice elements in risk reports may help individuals form more accurate risk perceptions.

Pharmacogenomic (PGx) Counseling: Exploring Participant Questions about PGx Test Results.

As pharmacogenomic (PGx) use in healthcare increases, a better understanding of patient needs will be necessary to guide PGx result delivery. The Coriell Personalized Medicine Collaborative (CPMC) is a prospective study investigating the utility of personalized medicine. Participants received online genetic risk reports for 27 potentially actionable complex diseases and 7 drug-gene pairs and could request free, telephone-based genetic counseling (GC). To explore the needs of individuals receiving PGx results, we conducted a retrospective qualitative review of inquiries from CPMC participants who requested counseling from March 2009 to February 2017. Eighty out of 690 (12%) total GC inquiries were focused on the discussion of PGx results, and six salient themes emerged: "general help", "issues with drugs", "relevant disease experience", "what do I do now?", "sharing results", and "other drugs". The number of reported medications with a corresponding PGx result and participant engagement were significantly associated with PGx GC requests (p < 0.01 and p < 0.02, respectively). Our work illustrates a range of questions raised by study participants receiving PGx test results, most of which were addressed by a genetic counselor with few requiring referrals to prescribing providers or pharmacists. These results further support a role for genetic counselors in the team-based approach to optimal PGx result delivery.

rs11670527 Upstream of ZNF264 Associated with Body Mass Index in the Coriell Personalized Medicine Collaborative.

INTRODUCTION: the effects of obesity on health are a concern for the military as they affect the fitness to serve of active service members, increase costs to the Military Health System, and reduce quality of life for veterans and beneficiaries. Although obesity can be influenced by behavioral and environmental factors, it has also been shown to be associated with genetic risk factors that are not fully understood. MATERIALS AND METHODS: we performed a genome-wide association study of 5,251 participants in the Coriell Personalized Medicine Collaborative, which includes 2,111 Air Force participants. We applied a generalized linear model, using principal component analysis to account for population structure, and analyzed single-variant associations with body mass index (BMI) as a continuous variable, using a Bonferroni-corrected P-value threshold to account for multiplicity. RESULTS: we identified one genome-wide significant locus, rs11670527, upstream of the ZNF264 gene on chromosome 19, associated with BMI. CONCLUSIONS: the finding of an association between rs11670527 and BMI adds to the growing body of literature characterizing the complex genetics of obesity. These efforts may eventually inform personalized interventions aimed at achieving and maintaining healthy weight.

Habitat-Specific Clock Variation and Its Consequence on Reproductive Fitness.

The circadian clock controls daily activities at the cellular and organismic level, allowing an organism to anticipate incoming stresses and to use resources accordingly. The circadian clock has therefore been considered a fitness trait in multiple organisms. However, the mechanism of how circadian clock variation influences organismal reproductive fitness is still not well understood. Here we describe habitat-specific clock variation (HSCV) of asexual reproduction in Neurospora discreta, a species that is adapted to 2 different habitats, under or above tree bark. African (AF) N. discreta strains, whose habitat is above the tree bark in light-dark (LD) conditions, display a higher rhythmicity index compared with North American (NA) strains, whose habitat is under the tree bark in constant dark (DD). Although AF-type strains demonstrated an overall fitness advantage under LD and DD conditions, NA-type strains exhibit a habitat-specific fitness advantage in DD over the LD condition. In addition, we show that allelic variation of the clock-controlled gene, Ubiquinol cytochrome c oxidoreductase (NEUDI_158280), plays a role in HSCV by modulating cellular reactive oxygen species levels. Our results demonstrate a mechanism by which local adaptation involving circadian clock regulation influences reproductive fitness.

Genomic evidence for shared common ancestry of East African hunting-gathering populations and insights into local adaptation.

Anatomically modern humans arose in Africa ∼300,000 years ago, but the demographic and adaptive histories of African populations are not well-characterized. Here, we have generated a genome-wide dataset from 840 Africans, residing in western, eastern, southern, and northern Africa, belonging to 50 ethnicities, and speaking languages belonging to four language families. In addition to agriculturalists and pastoralists, our study includes 16 populations that practice, or until recently have practiced, a hunting-gathering (HG) lifestyle. We observe that genetic structure in Africa is broadly correlated not only with geography, but to a lesser extent, with linguistic affiliation and subsistence strategy. Four East African HG (EHG) populations that are geographically distant from each other show evidence of common ancestry: the Hadza and Sandawe in Tanzania, who speak languages with clicks classified as Khoisan; the Dahalo in Kenya, whose language has remnant clicks; and the Sabue in Ethiopia, who speak an unclassified language. Additionally, we observed common ancestry between central African rainforest HGs and southern African San, the latter of whom speak languages with clicks classified as Khoisan. With the exception of the EHG, central African rainforest HGs, and San, other HG groups in Africa appear genetically similar to neighboring agriculturalist or pastoralist populations. We additionally demonstrate that infectious disease, immune response, and diet have played important roles in the adaptive landscape of African history. However, while the broad biological processes involved in recent human adaptation in Africa are often consistent across populations, the specific loci affected by selective pressures more often vary across populations.

Genetic and genomic stability across lymphoblastoid cell line expansions.

OBJECTIVE: Lymphoblastoid cell lines are widely used in genetic and genomic studies. Previous work has characterized variant stability in transformed culture and across culture passages. Our objective was to extend this work to evaluate single nucleotide polymorphism and structural variation across cell line expansions, which are commonly used in biorepository distribution. Our study used DNA and cell lines sampled from six research participants. We assayed genome-wide genetic variants and inferred structural variants for DNA extracted from blood, from transformed cell cultures, and from three generations of expansions. RESULTS: Single nucleotide variation was stable between DNA and expanded cell lines (ranging from 99.90 to 99.98% concordance). Structural variation was less consistent across expansions (median 33% concordance) with a noticeable decrease in later expansions. In summary, we demonstrate consistency between SNPs assayed from whole blood DNA and LCL DNA; however, more caution should be taken in using LCL DNA to study structural variation.

Adaptive Landscape of Protein Variation in Human Exomes.

The human genome contains hundreds of thousands of missense mutations. However, only a handful of these variants are known to be adaptive, which implies that adaptation through protein sequence change is an extremely rare phenomenon in human evolution. Alternatively, existing methods may lack the power to pinpoint adaptive variation. We have developed and applied an Evolutionary Probability Approach (EPA) to discover candidate adaptive polymorphisms (CAPs) through the discordance between allelic evolutionary probabilities and their observed frequencies in human populations. EPA reveals thousands of missense CAPs, which suggest that a large number of previously optimal alleles experienced a reversal of fortune in the human lineage. We explored nonadaptive mechanisms to explain CAPs, including the effects of demography, mutation rate variability, and negative and positive selective pressures in modern humans. Many nonadaptive hypotheses were tested, but failed to explain the data, which suggests that a large proportion of CAP alleles have increased in frequency due to beneficial selection. This suggestion is supported by the fact that a vast majority of adaptive missense variants discovered previously in humans are CAPs, and hundreds of CAP alleles are protective in genotype-phenotype association data. Our integrated phylogenomic and population genetic EPA approach predicts the existence of thousands of nonneutral candidate variants in the human proteome. We expect this collection to be enriched in beneficial variation. The EPA approach can be applied to discover candidate adaptive variation in any protein, population, or species for which allele frequency data and reliable multispecies alignments are available.

Precision Military Medicine: Conducting a multi-site clinical utility study of genomic and lifestyle risk factors in the United States Air Force.

Following several years enrolling disease-specific and otherwise healthy cohorts into the Coriell Personalized Medicine Collaborative, a prospective study aimed at evaluating the clinical utility of personal genomic information for common complex disease and pharmacogenomics, the Coriell Personalized Medicine Collaborative expanded to create a military cohort, specifically, the United States Air Force. Initial recruitment focused on Air Force Medical Service personnel and later expanded to include all Active Duty Air Force members and beneficiaries. Now in its 6th year, the study has produced a wide variety of insights, including optimal study design for military-sponsored genomic research, and discussion on genetic information sharing between and amongst Air Force study participants, civilian and military researchers, and the United States Department of Defense. Over the longer term, analyses will further contribute to the development of policies and processes relevant to clinical decision support and data sharing within the US military, and on-going work with the Air Force Medical Service sub-cohort will generate critical insights into how best to deploy useful genomic information in clinical care. Here we discuss challenges faced and critical success factors for military-civilian collaborations around genomic research.

e-GRASP: an integrated evolutionary and GRASP resource for exploring disease associations.

BACKGROUND: Genome-wide association studies (GWAS) have become a mainstay of biological research concerned with discovering genetic variation linked to phenotypic traits and diseases. Both discrete and continuous traits can be analyzed in GWAS to discover associations between single nucleotide polymorphisms (SNPs) and traits of interest. Associations are typically determined by estimating the significance of the statistical relationship between genetic loci and the given trait. However, the prioritization of bona fide, reproducible genetic associations from GWAS results remains a central challenge in identifying genomic loci underlying common complex diseases. Evolutionary-aware meta-analysis of the growing GWAS literature is one way to address this challenge and to advance from association to causation in the discovery of genotype-phenotype relationships. DESCRIPTION: We have created an evolutionary GWAS resource to enable in-depth query and exploration of published GWAS results. This resource uses the publically available GWAS results annotated in the GRASP2 database. The GRASP2 database includes results from 2082 studies, 177 broad phenotype categories, and ~8.87 million SNP-phenotype associations. For each SNP in e-GRASP, we present information from the GRASP2 database for convenience as well as evolutionary information (e.g., rate and timespan). Users can, therefore, identify not only SNPs with highly significant phenotype-association P-values, but also SNPs that are highly replicated and/or occur at evolutionarily conserved sites that are likely to be functionally important. Additionally, we provide an evolutionary-adjusted SNP association ranking (E-rank) that uses cross-species evolutionary conservation scores and population allele frequencies to transform P-values in an effort to enhance the discovery of SNPs with a greater probability of biologically meaningful disease associations. CONCLUSION: By adding an evolutionary dimension to the GWAS results available in the GRASP2 database, our e-GRASP resource will enable a more effective exploration of SNPs not only by the statistical significance of trait associations, but also by the number of studies in which associations have been replicated, and the evolutionary context of the associated mutations. Therefore, e-GRASP will be a valuable resource for aiding researchers in the identification of bona fide, reproducible genetic associations from GWAS results. This resource is freely available at http://www.mypeg.info/egrasp .

Challenges in Translating GWAS Results to Clinical Care.

Clinical genetic testing for Mendelian disorders is standard of care in many cases; however, it is less clear to what extent and in which situations clinical genetic testing may improve preventive efforts, diagnosis and/or prognosis of complex disease. One challenge is that much of the reported research relies on tag single nucleotide polymorphisms (SNPs) to act as proxies for assumed underlying functional variants that are not yet known. Here we use coronary artery disease and melanoma as case studies to evaluate how well reported genetic risk variants tag surrounding variants across population samples in the 1000 Genomes Project Phase 3 data. We performed a simulation study where we randomly assigned a "functional" variant and evaluated how often this simulated functional variant was correctly tagged in diverse population samples. Our results indicate a relatively large error rate when generalizing increased genetic risk of complex disease across diverse population samples, even when generalizing within geographic regions. Our results further highlight the importance of including diverse populations in genome-wide association studies. Future work focused on identifying functional variants will eliminate the need for tag SNPs; however, until functional variants are known, caution should be used in the interpretation of genetic risk for complex disease using tag SNPs.

An expanded pharmacogenomics warfarin dosing table with utility in generalised dosing guidance.

Pharmacogenomics (PGx) guided warfarin dosing, using a comprehensive dosing algorithm, is expected to improve dose optimisation and lower the risk of adverse drug reactions. As a complementary tool, a simple genotype-dosing table, such as in the US Food and Drug Administration (FDA) Coumadin drug label, may be utilised for general risk assessment of likely over- or under-anticoagulation on a standard dose of warfarin. This tool may be used as part of the clinical decision support for the interpretation of genetic data, serving as a first step in the anticoagulation therapy decision making process. Here we used a publicly available warfarin dosing calculator (www.warfarindosing.org) to create an expanded gene-based warfarin dosing table, the CPMC-WD table that includes nine genetic variants in CYP2C9, VKORC1, and CYP4F2. Using two datasets, a European American cohort (EUA, n=73) and the Quebec Warfarin Cohort (QWC, n=769), we show that the CPMC-WD table more accurately predicts therapeutic dose than the FDA table (51 % vs 33 %, respectively, in the EUA, McNemar's two-sided p=0.02; 52 % vs 37 % in the QWC, p<1×10(-6)). It also outperforms both the standard of care 5 mg/day dosing (51 % vs 34 % in the EUA, p=0.04; 52 % vs 31 % in the QWC, p<1×10(-6)) as well as a clinical-only algorithm (51 % vs 38 % in the EUA, trend p=0.11; 52 % vs 45 % in the QWC, p=0.003). This table offers a valuable update to the PGx dosing guideline in the drug label.

A Locus at 5q33.3 Confers Resistance to Tuberculosis in Highly Susceptible Individuals.

Immunosuppression resulting from HIV infection increases the risk of progression to active tuberculosis (TB) both in individuals newly exposed to Mycobacterium tuberculosis (MTB) and in those with latent infections. We hypothesized that HIV-positive individuals who do not develop TB, despite living in areas where it is hyperendemic, provide a model of natural resistance. We performed a genome-wide association study of TB resistance by using 581 HIV-positive Ugandans and Tanzanians enrolled in prospective cohort studies of TB; 267 of these individuals developed active TB, and 314 did not. A common variant, rs4921437 at 5q33.3, was significantly associated with TB (odds ratio = 0.37, p = 2.11 × 10(-8)). This variant lies within a genomic region that includes IL12B and is embedded in an H3K27Ac histone mark. The locus also displays consistent patterns of linkage disequilibrium across African populations and has signals of strong selection in populations from equatorial Africa. Along with prior studies demonstrating that therapy with IL-12 (the cytokine encoded in part by IL12B, associated with longer survival following MTB infection in mice deficient in CD4 T cells), our results suggest that this pathway might be an excellent target for the development of new modalities for treating TB, especially for HIV-positive individuals. Our results also indicate that studying extreme disease resistance in the face of extensive exposure can increase the power to detect associations in complex infectious disease.

Excavating Neandertal and Denisovan DNA from the genomes of Melanesian individuals.

Although Neandertal sequences that persist in the genomes of modern humans have been identified in Eurasians, comparable studies in people whose ancestors hybridized with both Neandertals and Denisovans are lacking. We developed an approach to identify DNA inherited from multiple archaic hominin ancestors and applied it to whole-genome sequences from 1523 geographically diverse individuals, including 35 previously unknown Island Melanesian genomes. In aggregate, we recovered 1.34 gigabases and 303 megabases of the Neandertal and Denisovan genome, respectively. We use these maps of archaic sequences to show that Neandertal admixture occurred multiple times in different non-African populations, characterize genomic regions that are significantly depleted of archaic sequences, and identify signatures of adaptive introgression.

Using the Coriell Personalized Medicine Collaborative Data to conduct a genome-wide association study of sleep duration.

Sleep is critical to health and functionality, and several studies have investigated the inherited component of insomnia and other sleep disorders using genome-wide association studies (GWAS). However, genome-wide studies focused on sleep duration are less common. Here, we used data from participants in the Coriell Personalized Medicine Collaborative (CPMC) (n = 4,401) to examine putative associations between self-reported sleep duration, demographic and lifestyle variables, and genome-wide single nucleotide polymorphism (SNP) data to better understand genetic contributions to variation in sleep duration. We employed stepwise ordered logistic regression to select our model and retained the following predictive variables: age, gender, weight, physical activity, physical activity at work, smoking status, alcohol consumption, ethnicity, and ancestry (as measured by principal components analysis) in our association testing. Several of our strongest candidate genes were previously identified in GWAS related to sleep duration (TSHZ2, ABCC9, FBXO15) and narcolepsy (NFATC2, SALL4). In addition, we have identified novel candidate genes for involvement in sleep duration including SORCS1 and ELOVL2. Our results demonstrate that the self-reported data collected through the CPMC are robust, and our genome-wide association analysis has identified novel candidate genes involved in sleep duration. More generally, this study contributes to a better understanding of the complexity of human sleep.

Common genetic risk for melanoma encourages preventive behavior change.

There is currently great interest in using genetic risk estimates for common disease in personalized healthcare. Here we assess melanoma risk-related preventive behavioral change in the context of the Coriell Personalized Medicine Collaborative (CPMC). As part of on-going reporting activities within the project, participants received a personalized risk assessment including information related to their own self-reported family history of melanoma and a genetic risk variant showing a moderate effect size (1.7, 3.0 respectively for heterozygous and homozygous individuals). Participants who opted to view their report were sent an optional outcome survey assessing risk perception and behavioral change in the months that followed. Participants that report family history risk, genetic risk, or both risk factors for melanoma were significantly more likely to increase skin cancer preventive behaviors when compared to participants with neither risk factor (ORs = 2.04, 2.79, 4.06 and p-values = 0.02, 2.86 × 10-5, 4.67 × 10-5, respectively), and we found the relationship between risk information and behavior to be partially mediated by anxiety. Genomic risk assessments appear to encourage positive behavioral change in a manner that is complementary to family history risk information and therefore may represent a useful addition to standard of care for melanoma prevention.