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.

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.

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.

Recent human adaptation: genomic approaches, interpretation and insights.

The recent availability of genomic data has spurred many genome-wide studies of human adaptation in different populations worldwide. Such studies have provided insights into novel candidate genes and pathways that are putatively involved in adaptation to different environments, diets and disease prevalence. However, much work is needed to translate these results into candidate adaptive variants that are biologically interpretable. In this Review, we discuss methods that may help to identify true biological signals of selection and studies that incorporate complementary phenotypic and functional data. We conclude with recommendations for future studies that focus on opportunities to use integrative genomics methodologies in human adaptation studies.

Operationalizing the Reciprocal Engagement Model of Genetic Counseling Practice: a Framework for the Scalable Delivery of Genomic Counseling and Testing.

With the advent of widespread genomic testing for diagnostic indications and disease risk assessment, there is increased need to optimize genetic counseling services to support the scalable delivery of precision medicine. Here, we describe how we operationalized the reciprocal engagement model of genetic counseling practice to develop a framework of counseling components and strategies for the delivery of genomic results. This framework was constructed based upon qualitative research with patients receiving genomic counseling following online receipt of potentially actionable complex disease and pharmacogenomics reports. Consultation with a transdisciplinary group of investigators, including practicing genetic counselors, was sought to ensure broad scope and applicability of these strategies for use with any large-scale genomic testing effort. We preserve the provision of pre-test education and informed consent as established in Mendelian/single-gene disease genetic counseling practice. Following receipt of genomic results, patients are afforded the opportunity to tailor the counseling agenda by selecting the specific test results they wish to discuss, specifying questions for discussion, and indicating their preference for counseling modality. The genetic counselor uses these patient preferences to set the genomic counseling session and to personalize result communication and risk reduction recommendations. Tailored visual aids and result summary reports divide areas of risk (genetic variant, family history, lifestyle) for each disease to facilitate discussion of multiple disease risks. Post-counseling, session summary reports are actively routed to both the patient and their physician team to encourage review and follow-up. Given the breadth of genomic information potentially resulting from genomic testing, this framework is put forth as a starting point to meet the need for scalable genetic counseling services in the delivery of precision medicine.

Outcomes of a Randomized Controlled Trial of Genomic Counseling for Patients Receiving Personalized and Actionable Complex Disease Reports.

There has been very limited study of patients with chronic disease receiving potentially actionable genomic based results or the utilization of genetic counselors in the online result delivery process. We conducted a randomized controlled trial on 199 patients with chronic disease each receiving eight personalized and actionable complex disease reports online. Primary study aims were to assess the impact of in-person genomic counseling on 1) causal attribution of disease risk, 2) personal awareness of disease risk, and 3) perceived risk of developing a particular disease. Of 98 intervention arm participants (mean age = 57.8; 39% female) randomized for in-person genomic counseling, 76 (78%) were seen. In contrast, control arm participants (n = 101; mean age = 58.5; 54% female) were initially not offered genomic counseling as part of the study protocol but were able to access in-person genomic counseling, if they requested it, 3-months post viewing of at least one test report and post-completion of the study-specific follow-up survey. A total of 64 intervention arm and 59 control arm participants completed follow-up survey measures. We found that participants receiving in-person genomic counseling had enhanced objective understanding of the genetic variant risk contribution for multiple complex diseases. Genomic counseling was associated with lowered participant causal beliefs in genetic influence across all eight diseases, compared to control participants. Our findings also illustrate that for the majority of diseases under study, intervention arm participants believed they knew their genetic risk status better than control arm subjects. Disease risk was modified for the majority during genomic counseling, due to the assessment of more comprehensive family history. In conclusion, for patients receiving personalized and actionable genomic results through a web portal, genomic counseling enhanced their objective understanding of the genetic variant risk contribution to multiple common diseases. These results support the development of additional genomic counseling interventions to ensure a high level of patient comprehension and improve patient-centered health outcomes.

Counselees' Perspectives of Genomic Counseling Following Online Receipt of Multiple Actionable Complex Disease and Pharmacogenomic Results: a Qualitative Research Study.

Genomic applications raise multiple challenges including the optimization of genomic counseling (GC) services as part of the results delivery process. More information on patients' motivations, preferences, and informational needs are essential to guide the development of new, more efficient practice delivery models that capitalize on the existing strengths of a limited genetic counseling workforce. Semi-structured telephone interviews were conducted with a subset of counselees from the Coriell Personalized Medicine Collaborative following online receipt of multiple personalized genomic test reports. Participants previously had either in-person GC (chronic disease cohort, n = 20; mean age 60 years) or telephone GC (community cohort, n = 31; mean age 46.8 years). Transcripts were analyzed using a Grounded Theory framework. Major themes that emerged from the interviews include 1) primary reasons for seeking GC were to clarify results, put results into perspective relative to other health-related concerns, and to receive personalized recommendations; 2) there is need for a more participant driven approach in terms of mode of GC communication (in-person, phone, video), and refining the counseling agenda pre-session; and 3) there was strong interest in the option of follow up GC. By clarifying counselees' expectations, views and desired outcomes, we have uncovered a need for a more participant-driven GC model when potentially actionable genomic results are received online.

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 .

Identifying Darwinian selection acting on different human APOL1 variants among diverse African populations.

Disease susceptibility can arise as a consequence of adaptation to infectious disease. Recent findings have suggested that higher rates of chronic kidney disease (CKD) in individuals with recent African ancestry might be attributed to two risk alleles (G1 and G2) at the serum-resistance-associated (SRA)-interacting-domain-encoding region of APOL1. These two alleles appear to have arisen adaptively, possibly as a result of their protective effects against human African trypanosomiasis (HAT), or African sleeping sickness. In order to explore the distribution of potential functional variation at APOL1, we studied nucleotide variation in 187 individuals across ten geographically and genetically diverse African ethnic groups with exposure to two Trypanosoma brucei subspecies that cause HAT. We observed unusually high levels of nonsynonymous polymorphism in the regions encoding the functional domains that are required for lysing parasites. Whereas allele frequencies of G2 were similar across all populations (3%-8%), the G1 allele was only common in the Yoruba (39%). Additionally, we identified a haplotype (termed G3) that contains a nonsynonymous change at the membrane-addressing-domain-encoding region of APOL1 and is present in all populations except for the Yoruba. Analyses of long-range patterns of linkage disequilibrium indicate evidence of recent selection acting on the G3 haplotype in Fulani from Cameroon. Our results indicate that the G1 and G2 variants in APOL1 are geographically restricted and that there might be other functional variants that could play a role in HAT resistance and CKD risk in African populations.

Genetic Knowledge Among Participants in the Coriell Personalized Medicine Collaborative.

Genetic literacy is essential for the effective integration of genomic information into healthcare; yet few recent studies have been conducted to assess the current state of this knowledge base. Participants in the Coriell Personalized Medicine Collaborative (CPMC), a prospective study assessing the impact of personalized genetic risk reports for complex diseases and drug response on behavior and health outcomes, completed genetic knowledge questionnaires and other surveys through an online portal. To assess the association between genetic knowledge and genetic education background, multivariate linear regression was performed. 4 062 participants completed a genetic knowledge and genetic education background questionnaire. Most were older (mean age: 50), Caucasian (90 %), female (59 %), highly educated (69 % bachelor's or higher), with annual household income over $100 000 (49 %). Mean percent correct was 76 %. Controlling for demographics revealed that health care providers, participants previously exposed to genetics, and participants with 'better than most' self-rated knowledge were significantly more likely to have a higher knowledge score (p < 0.001). Overall, genetic knowledge was high with previous genetic education experience predictive of higher genetic knowledge score. Education is likely to improve genetic literacy, an important component to expanded use of genomics in personalized medicine.

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.

Patterns of ancestry, signatures of natural selection, and genetic association with stature in Western African pygmies.

African Pygmy groups show a distinctive pattern of phenotypic variation, including short stature, which is thought to reflect past adaptation to a tropical environment. Here, we analyze Illumina 1M SNP array data in three Western Pygmy populations from Cameroon and three neighboring Bantu-speaking agricultural populations with whom they have admixed. We infer genome-wide ancestry, scan for signals of positive selection, and perform targeted genetic association with measured height variation. We identify multiple regions throughout the genome that may have played a role in adaptive evolution, many of which contain loci with roles in growth hormone, insulin, and insulin-like growth factor signaling pathways, as well as immunity and neuroendocrine signaling involved in reproduction and metabolism. The most striking results are found on chromosome 3, which harbors a cluster of selection and association signals between approximately 45 and 60 Mb. This region also includes the positional candidate genes DOCK3, which is known to be associated with height variation in Europeans, and CISH, a negative regulator of cytokine signaling known to inhibit growth hormone-stimulated STAT5 signaling. Finally, pathway analysis for genes near the strongest signals of association with height indicates enrichment for loci involved in insulin and insulin-like growth factor signaling.

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.

ursaPGx: a new R package to annotate pharmacogenetic star alleles using phased whole-genome sequencing data.

Long-read sequencing technologies offer new opportunities to generate high-confidence phased whole-genome sequencing data for robust pharmacogenetic annotation. Here, we describe a new user-friendly R package, ursaPGx, designed to accept multi-sample phased whole-genome sequencing data VCF input files and output star allele annotations for pharmacogenes annotated in PharmVar.

Colloquium paper: working toward a synthesis of archaeological, linguistic, and genetic data for inferring African population history.

Although Africa is the origin of modern humans, the pattern and distribution of genetic variation and correlations with cultural and linguistic diversity in Africa have been understudied. Recent advances in genomic technology, however, have led to genomewide studies of African samples. In this article, we discuss genetic variation in African populations contextualized with what is known about archaeological and linguistic variation. What emerges from this review is the importance of using independent lines of evidence in the interpretation of genetic and genomic data in the reconstruction of past population histories.

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.

Genome-wide insights into the patterns and determinants of fine-scale population structure in humans.

Studying genomic patterns of human population structure provides important insights into human evolutionary history and the relationship among populations, and it has significant practical implications for disease-gene mapping. Here we describe a principal component (PC)-based approach to studying intracontinental population structure in humans, identify the underlying markers mediating the observed patterns of fine-scale population structure, and infer the predominating evolutionary forces shaping local population structure. We applied this methodology to a data set of 650K SNPs genotyped in 944 unrelated individuals from 52 populations and demonstrate that, although typical PC analyses focus on the top axes of variation, substantial information about population structure is contained in lower-ranked PCs. We identified 18 significant PCs, some of which distinguish individual populations. In addition to visually representing sample clusters in PC biplots, we estimated the set of all SNPs significantly correlated with each of the most informative axes of variation. These polymorphisms, unlike ancestry-informative markers (AIMs), constitute a much larger set of loci that drive genomic signatures of population structure. The genome-wide distribution of these significantly correlated markers can largely be accounted for by the stochastic effects of genetic drift, although significant clustering does occur in genomic regions that have been previously implicated as targets of recent adaptive evolution.

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 [...].