Challenges and disparities in the application of personalized genomic medicine to populations with African ancestry

Equitable machine learning counteracts ancestral bias in precision medicine

Gold standard genomic datasets severely under-represent non-European populations, leading to inequities and a limited understanding of human disease. Therapeutics and outcomes remain hidden because we lack insights that could be gained from analyzing ancestrally diverse genomic data. To address this significant gap, we present PhyloFrame, a machine learning method for equitable genomic precision medicine. PhyloFrame corrects for ancestral bias by integrating functional interaction networks and population genomics data with transcriptomic training data. Application of PhyloFrame to breast, thyroid, and uterine cancers shows marked improvements in predictive power across all ancestries, less model overfitting, and a higher likelihood of identifying known cancer-related genes. Validation in fourteen ancestrally diverse datasets demonstrates that PhyloFrame is better able to adjust for ancestry bias across all populations. The ability to provide accurate predictions for underrepresented groups, in particular, is substantially increased. Analysis of performance in the most diverse continental ancestry group, African, illustrates how phylogenetic distance from training data negatively impacts model performance, as well as PhyloFrame's capacity to mitigate these effects. These results demonstrate how equitable artificial intelligence (AI) approaches can mitigate ancestral bias in training data and contribute to equitable representation in medical research.

Improving diagnostic precision in primary ovarian insufficiency using comprehensive genetic and autoantibody testing

STUDY QUESTION

Is it possible to find the cause of primary ovarian insufficiency (POI) in more women by extensive screening?

SUMMARY ANSWER

Adding next generation sequencing techniques including a POI-associated gene panel, extended whole exome sequencing data, as well as specific autoantibody assays to the recommended diagnostic investigations increased the determination of a potential etiological diagnosis of POI from 11% to 41%.

WHAT IS KNOWN ALREADY

POI affects ∼1% of women. Clinical presentations and pathogenic mechanisms are heterogeneous and include genetic, autoimmune, and environmental factors, but the underlying etiology remains unknown in the majority of cases.

STUDY DESIGN, SIZE, DURATION

Prospective cross-sectional study of 100 women with newly diagnosed POI of unknown cause consecutively referred to Haukeland University Hospital, Bergen, Norway, January 2019 to December 2021.

PARTICIPANTS/MATERIALS, SETTING, METHODS

In addition to standard recommended diagnostic investigations including screening for chromosomal anomalies and premutations in the fragile X mental retardation 1 gene (FMR1) we used whole exome sequencing, including targeted analysis of 103 ovarian-related genes, and assays of autoantibodies against steroid cell antigens.

MAIN RESULTS AND THE ROLE OF CHANCE

We identified chromosomal aberrations in 8%, FMR1 premutations in 3%, genetic variants related to POI in 16%, and autoimmune POI in 3%. Furthermore in 11% we identified POI associated genetic Variants of unknown signifcance (VUS). A homozygous pathogenic variant in the ZSWIM7 gene (NM_001042697.2) was found in two women, corroborating this as a novel cause of monogenic POI. No associations between phenotypes and genotypes were found.

LIMITATIONS, REASONS FOR CAUTION

Use of candidate genetic and autoimmune markers limit the possibility to discover new markers. To further investigate the genetic variants, family studies would have been useful. We found a relatively high proportion of genetic variants in women from Africa and lack of genetic diversity in the genomic databases can impact diagnostic accuracy.

WIDER IMPLICATIONS OF THE FINDINGS

Since no specific clinical or biochemical markers predicted the underlying cause of POI discussion of which tests should be part of diagnostic screening in clinical practice remains open. New technology has altered the availability and effectiveness of genetic testing, and cost-effectiveness analyses are required to aid sustainable diagnostics.

STUDY FUNDING/COMPETING INTEREST(S)

The study was supported by grants and fellowships from Stiftelsen Kristian Gerhard Jebsen, the Novonordisk Foundation, the Norwegian Research Council, University of Bergen, and the Regional Health Authorities of Western Norway. The authors declare no conflict of interest.

TRIAL REGISTRATION NUMBER

NCT04082169.

Transcriptomics and chromatin accessibility in multiple African population samples

Mapping the functional human genome and impact of genetic variants is often limited to European-descendent population samples. To aid in overcoming this limitation, we measured gene expression using RNA sequencing in lymphoblastoid cell lines (LCLs) from 599 individuals from six African populations to identify novel transcripts including those not represented in the hg38 reference genome. We used whole genomes from the 1000 Genomes Project and 164 Maasai individuals to identify 8,881 expression and 6,949 splicing quantitative trait loci (eQTLs/sQTLs), and 2,611 structural variants associated with gene expression (SV-eQTLs). We further profiled chromatin accessibility using ATAC-Seq in a subset of 100 representative individuals, to identity chromatin accessibility quantitative trait loci (caQTLs) and allele-specific chromatin accessibility, and provide predictions for the functional effect of 78.9 million variants on chromatin accessibility. Using this map of eQTLs and caQTLs we fine-mapped GWAS signals for a range of complex diseases. Combined, this work expands global functional genomic data to identify novel transcripts, functional elements and variants, understand population genetic history of molecular quantitative trait loci, and further resolve the genetic basis of multiple human traits and disease.

Machine Learning-Guided Protein Engineering

Recent progress in engineering highly promising biocatalysts has increasingly involved machine learning methods. These methods leverage existing experimental and simulation data to aid in the discovery and annotation of promising enzymes, as well as in suggesting beneficial mutations for improving known targets. The field of machine learning for protein engineering is gathering steam, driven by recent success stories and notable progress in other areas. It already encompasses ambitious tasks such as understanding and predicting protein structure and function, catalytic efficiency, enantioselectivity, protein dynamics, stability, solubility, aggregation, and more. Nonetheless, the field is still evolving, with many challenges to overcome and questions to address. In this Perspective, we provide an overview of ongoing trends in this domain, highlight recent case studies, and examine the current limitations of machine learning-based methods. We emphasize the crucial importance of thorough experimental validation of emerging models before their use for rational protein design. We present our opinions on the fundamental problems and outline the potential directions for future research.

Education and electronic medical records and genomics network, challenges, and lessons learned from a large-scale clinical trial using polygenic risk scores

Polygenic risk scores (PRS) have potential to improve health care by identifying individuals that have elevated risk for common complex conditions. Use of PRS in clinical practice, however, requires careful assessment of the needs and capabilities of patients, providers, and health care systems. The electronic Medical Records and Genomics (eMERGE) network is conducting a collaborative study which will return PRS to 25,000 pediatric and adult participants. All participants will receive a risk report, potentially classifying them as high risk (∼2-10% per condition) for 1 or more of 10 conditions based on PRS. The study population is enriched by participants from racial and ethnic minority populations, underserved populations, and populations who experience poorer medical outcomes. All 10 eMERGE clinical sites conducted focus groups, interviews, and/or surveys to understand educational needs among key stakeholders-participants, providers, and/or study staff. Together, these studies highlighted the need for tools that address the perceived benefit/value of PRS, types of education/support needed, accessibility, and PRS-related knowledge and understanding. Based on findings from these preliminary studies, the network harmonized training initiatives and formal/informal educational resources. This paper summarizes eMERGE's collective approach to assessing educational needs and developing educational approaches for primary stakeholders. It discusses challenges encountered and solutions provided.

Potential pathogenic germline variant reporting from tumor comprehensive genomic profiling complements classic approaches to germline testing

Existing guidance regarding clinically informed germline testing for patients with cancer is effective for evaluation of classic hereditary cancer syndromes and established gene/cancer type associations. However, current screening methods may miss patients with rare, reduced penetrance, or otherwise occult hereditary risk. Secondary finding of suspected germline variants that may confer inherited cancer risk via tumor comprehensive genomic profiling (CGP) has the potential to help address these limitations. However, reporting practices for secondary finding of germline variants are inconsistent, necessitating solutions for transparent and coherent communication of these potentially important findings. A workflow for improved confidence detection and clear reporting of potential pathogenic germline variants (PPGV) in select cancer susceptibility genes (CSG) was applied to a research dataset from real-world clinical tumor CGP of > 125,000 patients with advanced cancer. The presence and patterns of PPGVs identified across tumor types was assessed with a focus on scenarios in which traditional clinical germline evaluation may have been insufficient to capture genetic risk. PPGVs were identified in 9.7% of tumor CGP cases using tissue- and liquid-based assays across a broad range of cancer types, including in a number of "off-tumor" contexts. Overall, PPGVs were identified in a similar proportion of cancers with National Comprehensive Cancer Network (NCCN) recommendations for germline testing regardless of family history (11%) as in all other cancer types (9%). These findings suggest that tumor CGP can serve as a tool that is complementary to traditional germline genetic evaluation in helping to ascertain inherited susceptibility in patients with advanced cancer.

Unraveling patient heterogeneity in complex diseases through individualized co-expression networks: a perspective

This perspective highlights the potential of individualized networks as a novel strategy for studying complex diseases through patient stratification, enabling advancements in precision medicine. We emphasize the impact of interpatient heterogeneity resulting from genetic and environmental factors and discuss how individualized networks improve our ability to develop treatments and enhance diagnostics. Integrating system biology, combining multimodal information such as genomic and clinical data has reached a tipping point, allowing the inference of biological networks at a single-individual resolution. This approach generates a specific biological network per sample, representing the individual from which the sample originated. The availability of individualized networks enables applications in personalized medicine, such as identifying malfunctions and selecting tailored treatments. In essence, reliable, individualized networks can expedite research progress in understanding drug response variability by modeling heterogeneity among individuals and enabling the personalized selection of pharmacological targets for treatment. Therefore, developing diverse and cost-effective approaches for generating these networks is crucial for widespread application in clinical services.

Inborn Errors of Immunity in Hidradenitis Suppurativa Pathogenesis and Disease Burden

Hidradenitis suppurativa (HS), also known as Verneuil's disease and acne inversa, is a prevalent, debilitating, and understudied inflammatory skin disease. It is marked by repeated bouts of pathological inflammation causing pain, hyperplasia, aberrant healing, and fibrosis. HS is difficult to manage and has many unmet medical needs. There is clinical and pharmacological evidence for extensive etiological heterogeneity with HS, suggesting that this clinical diagnosis is capturing a spectrum of disease entities. Human genetic studies provide robust insight into disease pathogenesis. They also can be used to resolve etiological heterogeneity and to identify drug targets. However, HS has not been extensively investigated with well-powered genetic studies. Here, we review what is known about its genetic architecture. We identify overlap in molecular, cellular, and clinical features between HS and inborn errors of immunity (IEI). This evidence indicates that HS may be an underrecognized component of IEI and suggests that undiagnosed IEI are present in HS cohorts. Inborn errors of immunity represent a salient opportunity for rapidly resolving the immunological landscape of HS pathogenesis, for prioritizing drug repurposing studies, and for improving the clinical management of HS.

Genomic diagnosis and care co-ordination for monogenic inflammatory bowel disease in children and adults: consensus guideline on behalf of the British Society of Gastroenterology and British Society of Paediatric Gastroenterology, Hepatology and Nutrition

Genomic medicine enables the identification of patients with rare or ultra-rare monogenic forms of inflammatory bowel disease (IBD) and supports clinical decision making. Patients with monogenic IBD frequently experience extremely early onset of treatment-refractory disease, with complex extraintestinal disease typical of immunodeficiency. Since more than 100 monogenic disorders can present with IBD, new genetic disorders and variants are being discovered every year, and as phenotypic expression of the gene defects is variable, adaptive genomic technologies are required. Monogenic IBD has become a key area to establish the concept of precision medicine. Clear guidance and standardised, affordable applications of genomic technologies are needed to implement exome or genome sequencing in clinical practice. This joint British Society of Gastroenterology and British Society of Paediatric Gastroenterology, Hepatology and Nutrition guideline aims to ensure that testing resources are appropriately applied to maximise the benefit to patients on a national scale, minimise health-care disparities in accessing genomic technologies, and optimise resource use. We set out the structural requirements for genomic medicine as part of a multidisciplinary team approach. Initiation of genomic diagnostics should be guided by diagnostic criteria for the individual patient, in particular the age of IBD onset and the patient's history, and potential implications for future therapies. We outline the diagnostic care pathway for paediatric and adult patients. This guideline considers how to handle clinically actionable findings in research studies and the impact of consumer-based genomics for monogenic IBD. This document was developed by multiple stakeholders, including UK paediatric and adult gastroenterology physicians, immunologists, transplant specialists, clinical geneticists, scientists, and research leads of UK genetic programmes, in partnership with patient representatives of several IBD and rare disease charities.

Evaluation of a whole-exome sequencing pipeline and benchmarking of causal germline variant prioritizers

Most causal variants of Mendelian diseases are exonic. Whole-exome sequencing (WES) has become the diagnostic gold standard, but causative variant prioritization constitutes a bottleneck. Here we assessed an in-house sample-to-sequence pipeline and benchmarked free prioritization tools for germline causal variants from WES data. WES of 61 unselected patients with a known genetic disease cause was obtained. Variant prioritizations were performed by diverse tools and recorded to obtain a diagnostic yield when the causal variant was present in the first, fifth, and 10th top rankings. A fraction of causal variants was not captured by WES (8.2%) or did not pass the quality control criteria (13.1%). Most of the applications inspected were unavailable or had technical limitations, leaving nine tools for complete evaluation. Exomiser performed best in the top first rankings, while LIRICAL led in the top fifth rankings. Based on the more conservative top 10th rankings, Xrare had the highest diagnostic yield, followed by a three-way tie among Exomiser, LIRICAL, and PhenIX, then followed by AMELIE, TAPES, Phen-Gen,  AIVar, and VarNote-PAT. Xrare, Exomiser, LIRICAL, and PhenIX are the most efficient options for variant prioritization in real patient WES data.

Central resources of variant discovery and annotation and its role in precision medicine

Rapid technological advancement in high-throughput genomics, microarray, and deep sequencing technologies has accelerated the possibility of more complex precision medicine research using large amounts of heterogeneous health-related data from patients, including genomic variants. Genomic variants can be identified and annotated based on the reference human genome either within the sequence as a whole or in a putative functional genomic element. The American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) mutually created standards and guidelines for the appraisal of proof to expand consistency and straightforwardness in clinical variation interpretations. Various efforts toward precision medicine have been facilitated by many national and international public databases that classify and annotate genomic variation. In the present study, several resources are highlighted with recognition and data spreading of clinically important genetic variations.

Whole Exome Sequencing in South Africa: Stakeholder Views on Return of Individual Research Results and Incidental Findings

The use of whole exome sequencing (WES) in medical research is increasing in South Africa (SA), raising important questions about whether and which individual genetic research results, particularly incidental findings, should be returned to patients. Whilst some commentaries and opinions related to the topic have been published in SA, there is no qualitative data on the views of professional stakeholders on this topic. Seventeen participants including clinicians, genomics researchers, and genetic counsellors (GCs) were recruited from the Western Cape in SA. Semi-structured interviews were conducted, and the transcripts analysed using the framework approach for data analysis. Current roadblocks for the clinical adoption of WES in SA include a lack of standardised guidelines; complexities relating to variant interpretation due to lack of functional studies and underrepresentation of people of African ancestry in the reference genome, population and variant databases; lack of resources and skilled personnel for variant confirmation and follow-up. Suggestions to overcome these barriers include obtaining funding and buy-in from the private and public sectors and medical insurance companies; the generation of a locally relevant reference genome; training of health professionals in the field of genomics and bioinformatics; and multidisciplinary collaboration. Participants emphasised the importance of upscaling the accessibility to and training of GCs, as well as upskilling of clinicians and genetic nurses for return of genetic data in collaboration with GCs and medical geneticists. Future research could focus on exploring the development of stakeholder partnerships for increased access to trained specialists as well as community engagement and education, alongside the development of guidelines for result disclosure.

Demonstrating an approach for evaluating synthetic geospatial and temporal epidemiologic data utility: results from analyzing >1.8 million SARS-CoV-2 tests in the United States National COVID Cohort Collaborative (N3C)

OBJECTIVE

This study sought to evaluate whether synthetic data derived from a national coronavirus disease 2019 (COVID-19) dataset could be used for geospatial and temporal epidemic analyses.

MATERIALS AND METHODS

Using an original dataset (n = 1 854 968 severe acute respiratory syndrome coronavirus 2 tests) and its synthetic derivative, we compared key indicators of COVID-19 community spread through analysis of aggregate and zip code-level epidemic curves, patient characteristics and outcomes, distribution of tests by zip code, and indicator counts stratified by month and zip code. Similarity between the data was statistically and qualitatively evaluated.

RESULTS

In general, synthetic data closely matched original data for epidemic curves, patient characteristics, and outcomes. Synthetic data suppressed labels of zip codes with few total tests (mean = 2.9 ± 2.4; max = 16 tests; 66% reduction of unique zip codes). Epidemic curves and monthly indicator counts were similar between synthetic and original data in a random sample of the most tested (top 1%; n = 171) and for all unsuppressed zip codes (n = 5819), respectively. In small sample sizes, synthetic data utility was notably decreased.

DISCUSSION

Analyses on the population-level and of densely tested zip codes (which contained most of the data) were similar between original and synthetically derived datasets. Analyses of sparsely tested populations were less similar and had more data suppression.

CONCLUSION

In general, synthetic data were successfully used to analyze geospatial and temporal trends. Analyses using small sample sizes or populations were limited, in part due to purposeful data label suppression-an attribute disclosure countermeasure. Users should consider data fitness for use in these cases.

Is Our Science Representative? A Systematic Review of Racial and Ethnic Diversity in Orthopaedic Clinical Trials from 2000 to 2020

BACKGROUND

A lack of racial and ethnic representation in clinical trials may limit the generalizability of the orthopaedic evidence base as it applies to patients in underrepresented minority populations and perpetuate existing disparities in use, complications, or functional outcomes. Although some commentators have implied the need for mandatory race or ethnicity reporting across all orthopaedic trials, the usefulness of race or ethnic reporting likely depends on the specific topic, prior evidence of disparities, and individualized study hypotheses.

QUESTIONS/PURPOSES

In a systematic review, we asked: (1) What proportion of orthopaedic clinical trials report race or ethnicity data, and of studies that do, how many report data regarding social covariates or genomic testing? (2) What trends and associations exist for racial and ethnic reporting among these trials between 2000 and 2020? (3) What is the racial or ethnic representation of United States trial participants compared with that reported in the United States Census?

METHODS

We performed a systematic review of randomized controlled trials with human participants published in three leading general-interest orthopaedic journals that focus on clinical research: The Journal of Bone and Joint Surgery, American Volume; Clinical Orthopaedics and Related Research; and Osteoarthritis and Cartilage. We searched the PubMed and Embase databases using the following inclusion criteria: English-language studies, human studies, randomized controlled trials, publication date from 2000 to 2020, and published in Clinical Orthopaedics and Related Research; The Journal of Bone and Joint Surgery, American Volume; or Osteoarthritis and Cartilage. Primary outcome measures included whether studies reported participant race or ethnicity, other social covariates (insurance status, housing or homelessness, education and literacy, transportation, income and employment, and food security and nutrition), and genomic testing. The secondary outcome measure was the racial and ethnic categorical distribution of the trial participants included in the studies reporting race or ethnicity. From our search, 1043 randomized controlled trials with 184,643 enrolled patients met the inclusion criteria. Among these studies, 21% (223 of 1043) had a small (< 50) sample size, 56% (581 of 1043) had a medium (50 to 200) sample size, and 23% (239 of 1043) had a large (> 200) sample size. Fourteen percent (141 of 1043) were based in the Northeast United States, 9.2% (96 of 1043) were in the Midwest, 4.7% (49 of 1043) were in the West, 7.2% (75 of 1043) were in the South, and 65% (682 of 1043) were outside the United States. We calculated the overall proportion of studies meeting the inclusion criteria that reported race or ethnicity. Then among the subset of studies reporting race or ethnicity, we determined the overall rate and distribution of social covariates and genomic testing reporting. We calculated the proportion of studies reporting race or ethnicity that also reported a difference in outcome by race or ethnicity. We calculated the proportion of studies reporting race or ethnicity by each year in the study period. We also calculated the proportions and 95% CIs of individual patients in each racial or ethnic category of the studies meeting the inclusion criteria.

RESULTS

During the study period (2000 to 2020), 8.5% (89 of 1043) of studies reported race or ethnicity. Of the trials reporting this factor, 4.5% (four of 89) reported insurance status, 15% (13 of 89) reported income, 4.5% (four of 89) reported housing or homelessness, 18% (16 of 89) reported education and literacy, 0% (0 of 89) reported transportation, and 2.2% (two of 89) reported food security or nutrition of trial participants. Seventy-eight percent (69 of 89) of trials reported no social covariates, while 22% (20 of 89) reported at least one. However, 0% (0 of 89) of trials reported genomic testing. Additionally, 5.6% (five of 89) of these trials reported a difference in outcomes by race or ethnicity. The proportion of studies reporting race or ethnicity increased, on average, by 0.6% annually (95% CI 0.2% to 1.0%; p = 0.02). After controlling for potentially confounding variables such as funding source, we found that studies with an increased sample size were more likely to report data by race or ethnicity; location in North America overall, Europe, Asia, and Australia or New Zealand (compared with the Northeast United States) were less likely to; and specialty-topic studies (compared with general orthopaedics research) were less likely to. Our sample of United States trials contained 18.9% more white participants than that reported in the United States Census (95% CI 18.4% to 19.4%; p < 0.001), 5.0% fewer Black participants (95% CI 4.6% to 5.3%; p < 0.001), 17.0% fewer Hispanic participants (95% CI 16.8% to 17.1%; p < 0.001), 5.3% fewer Asian participants (95% CI 5.2% to 5.4%; p < 0.001), and 7.5% more participants from other groups (95% CI 7.2% to 7.9%; p < 0.001).

CONCLUSION

Reporting of race or ethnicity data in orthopaedic clinical trials is low compared with other medical fields, although the proportion of diseases warranting this reporting might be lower in orthopaedics.

CLINICAL RELEVANCE

Investigators should initiate discussions about race and ethnicity reporting in the early stages of clinical trial development by surveying available published evidence for relevant health disparities, social determinants, and, when warranted, genomic risk factors. The decision to include or exclude race and ethnicity data in study protocols should be based on specific hypotheses, necessary statistical power, and an appreciation for unmeasured confounding. Future studies should evaluate cost-efficient mechanisms for obtaining baseline social covariate data and investigate researcher perspectives on current administrative workflows and decision-making algorithms for race and ethnicity reporting.

Whole-genome sequencing of 1,171 elderly admixed individuals from São Paulo, Brazil

As whole-genome sequencing (WGS) becomes the gold standard tool for studying population genomics and medical applications, data on diverse non-European and admixed individuals are still scarce. Here, we present a high-coverage WGS dataset of 1,171 highly admixed elderly Brazilians from a census-based cohort, providing over 76 million variants, of which ~2 million are absent from large public databases. WGS enables identification of ~2,000 previously undescribed mobile element insertions without previous description, nearly 5 Mb of genomic segments absent from the human genome reference, and over 140 alleles from HLA genes absent from public resources. We reclassify and curate pathogenicity assertions for nearly four hundred variants in genes associated with dominantly-inherited Mendelian disorders and calculate the incidence for selected recessive disorders, demonstrating the clinical usefulness of the present study. Finally, we observe that whole-genome and HLA imputation could be significantly improved compared to available datasets since rare variation represents the largest proportion of input from WGS. These results demonstrate that even smaller sample sizes of underrepresented populations bring relevant data for genomic studies, especially when exploring analyses allowed only by WGS.

Whole genome sequencing (WGS) data on non-European and admixed individuals remains scarce. Here, the authors analyse WGS data from 1,171 admixed elderly Brazilians from a census cohort, characterising population-specific genetic variation and exploring the clinical utility of this expanded dataset.

A guide for the diagnosis of rare and undiagnosed disease: beyond the exome

Rare diseases affect 30 million people in the USA and more than 300-400 million worldwide, often causing chronic illness, disability, and premature death. Traditional diagnostic techniques rely heavily on heuristic approaches, coupling clinical experience from prior rare disease presentations with the medical literature. A large number of rare disease patients remain undiagnosed for years and many even die without an accurate diagnosis. In recent years, gene panels, microarrays, and exome sequencing have helped to identify the molecular cause of such rare and undiagnosed diseases. These technologies have allowed diagnoses for a sizable proportion (25-35%) of undiagnosed patients, often with actionable findings. However, a large proportion of these patients remain undiagnosed. In this review, we focus on technologies that can be adopted if exome sequencing is unrevealing. We discuss the benefits of sequencing the whole genome and the additional benefit that may be offered by long-read technology, pan-genome reference, transcriptomics, metabolomics, proteomics, and methyl profiling. We highlight computational methods to help identify regionally distant patients with similar phenotypes or similar genetic mutations. Finally, we describe approaches to automate and accelerate genomic analysis. The strategies discussed here are intended to serve as a guide for clinicians and researchers in the next steps when encountering patients with non-diagnostic exomes.

Genome-wide analysis of copy number variants and normal facial variation in a large cohort of Bantu Africans

Similarity in facial characteristics between relatives suggests a strong genetic component underlies facial variation. While there have been numerous studies of the genetics of facial abnormalities and, more recently, single nucleotide polymorphism (SNP) genome-wide association studies (GWASs) of normal facial variation, little is known about the role of genetic structural variation in determining facial shape. In a sample of Bantu African children, we found that only 9% of common copy number variants (CNVs) and 10-kb CNV analysis windows are well tagged by SNPs (r2 ≥ 0.8), indicating that associations with our internally called CNVs were not captured by previous SNP-based GWASs. Here, we present a GWAS and gene set analysis of the relationship between normal facial variation and CNVs in a sample of Bantu African children. We report the top five regions, which had p values ≤ 9.35 × 10-6 and find nominal evidence of independent CNV association (p < 0.05) in three regions previously identified in SNP-based GWASs. The CNV region with strongest association (p = 1.16 × 10-6, 55 losses and seven gains) contains NFATC1, which has been linked to facial morphogenesis and Cherubism, a syndrome involving abnormal lower facial development. Genomic loss in the region is associated with smaller average lower facial depth. Importantly, new loci identified here were not identified in a SNP-based GWAS, suggesting that CNVs are likely involved in determining facial shape variation. Given the plethora of SNP-based GWASs, calling CNVs from existing data may be a relatively inexpensive way to aid in the study of complex traits.

Peptide ancestry informative markers in uterine neoplasms from women of European, African, and Asian ancestry

Characterization of ancestry-linked peptide variants in disease-relevant patient tissues represents a foundational step to connect patient ancestry with disease pathogenesis. Nonsynonymous single-nucleotide polymorphisms encoding missense substitutions within tryptic peptides exhibiting high allele frequencies in European, African, and East Asian populations, termed peptide ancestry informative markers (pAIMs), were prioritized from 1000 genomes. In silico analysis identified that as few as 20 pAIMs can determine ancestry proportions similarly to >260K SNPs (R² = 0.99). Multiplexed proteomic analysis of >100 human endometrial cancer cell lines and uterine leiomyoma tissues combined resulted in the quantitation of 62 pAIMs that correlate with patient race and genotype-confirmed ancestry. Candidates include a D451E substitution in GC vitamin D-binding protein previously associated with altered vitamin D levels in African and European populations. pAIMs will support generalized proteoancestry assessment as well as efforts investigating the impact of ancestry on the human proteome and how this relates to the pathogenesis of uterine neoplasms.

Whole-exome analysis in Tunisian Imazighen and Arabs shows the impact of demography in functional variation

Human populations are genetically affected by their demographic history, which shapes the distribution of their functional genomic variation. However, the genetic impact of recent demography is debated. This issue has been studied in different populations, but never in North Africans, despite their relevant cultural and demographic diversity. In this study we address the question by analyzing new whole-exome sequences from two culturally different Tunisian populations, an isolated Amazigh population and a close non-isolated Arab-speaking population, focusing on the distribution of functional variation. Both populations present clear differences in their variant frequency distribution, in general and for putatively damaging variation. This suggests a relevant effect in the Amazigh population of genetic isolation, drift, and inbreeding, pointing to relaxed purifying selection. We also discover the enrichment in Imazighen of variation associated to specific diseases or phenotypic traits, but the scarce genetic and biomedical data in the region limits further interpretation. Our results show the genomic impact of recent demography and reveal a clear genetic differentiation probably related to culture. These findings highlight the importance of considering cultural and demographic heterogeneity within North Africa when defining population groups, and the need for more data to improve knowledge on the region's health and disease landscape.

Monogenic Diabetes in Youth With Presumed Type 2 Diabetes: Results From the Progress in Diabetes Genetics in Youth (ProDiGY) Collaboration

OBJECTIVE

Maturity-onset diabetes of the young (MODY) is frequently misdiagnosed as type 1 or type 2 diabetes. Correct diagnosis may result in a change in clinical treatment and impacts prediction of complications and familial risk. In this study, we aimed to assess the prevalence of MODY in multiethnic youth under age 20 years with a clinical diagnosis of type 2 diabetes.

RESEARCH DESIGN AND METHODS

We evaluated whole-exome sequence data of youth with a clinical diagnosis of type 2 diabetes. We considered participants to have MODY if they carried a MODY gene variant classified as likely pathogenic (LP) or pathogenic (P) according to current guidelines.

RESULTS

Of 3,333 participants, 93 (2.8%) carried an LP/P variant in HNF4A (16 participants), GCK (23), HNF1A (44), PDX1 (5), INS (4), and CEL (1). Compared with those with no LP/P variants, youth with MODY had a younger age at diagnosis (12.9 ± 2.5 vs. 13.6 ± 2.3 years, P = 0.002) and lower fasting C-peptide levels (3.0 ± 1.7 vs. 4.7 ± 3.5 ng/mL, P < 0.0001). Youth with MODY were less likely to have hypertension (6.9% vs. 19.5%, P = 0.007) and had higher HDL cholesterol (43.8 vs. 39.7 mg/dL, P = 0.006).

CONCLUSIONS

By comprehensively sequencing the coding regions of all MODY genes, we identified MODY in 2.8% of youth with clinically diagnosed type 2 diabetes; importantly, in 89% (n = 83) the specific diagnosis would have changed clinical management. No clinical criterion reliably separated the two groups. New tools are needed to find ideal criteria for selection of individuals for genetic testing.

Demonstrating an approach for evaluating synthetic geospatial and temporal epidemiologic data utility: Results from analyzing >1.8 million SARS-CoV-2 tests in the United States National COVID Cohort Collaborative (N3C)

OBJECTIVE

To evaluate whether synthetic data derived from a national COVID-19 data set could be used for geospatial and temporal epidemic analyses.

MATERIALS AND METHODS

Using an original data set (n=1,854,968 SARS-CoV-2 tests) and its synthetic derivative, we compared key indicators of COVID-19 community spread through analysis of aggregate and zip-code level epidemic curves, patient characteristics and outcomes, distribution of tests by zip code, and indicator counts stratified by month and zip code. Similarity between the data was statistically and qualitatively evaluated.

RESULTS

In general, synthetic data closely matched original data for epidemic curves, patient characteristics, and outcomes. Synthetic data suppressed labels of zip codes with few total tests (mean=2.9±2.4; max=16 tests; 66% reduction of unique zip codes). Epidemic curves and monthly indicator counts were similar between synthetic and original data in a random sample of the most tested (top 1%; n=171) and for all unsuppressed zip codes (n=5,819), respectively. In small sample sizes, synthetic data utility was notably decreased.

DISCUSSION

Analyses on the population-level and of densely-tested zip codes (which contained most of the data) were similar between original and synthetically-derived data sets. Analyses of sparsely-tested populations were less similar and had more data suppression.

CONCLUSION

In general, synthetic data were successfully used to analyze geospatial and temporal trends. Analyses using small sample sizes or populations were limited, in part due to purposeful data label suppression -an attribute disclosure countermeasure. Users should consider data fitness for use in these cases.

Biased pathogenic assertions of loss of function variants challenge molecular diagnosis of admixed individuals

Diagnosis of individuals affected by monogenic disorders was significantly improved by next-generation sequencing targeting clinically relevant genes. Whole exomes yield a large number of variants that require several filtering steps, prioritization, and pathogenicity classification. Among the criteria recommended by ACMG, those that rely on population databases critically affect analyses of individuals with underrepresented ancestries. Population-specific allelic frequencies need consideration when characterizing potential deleteriousness of variants. An orthogonal input for classification is annotation of variants previously classified as pathogenic as a criterion that provide supporting evidence widely sourced at ClinVar. We used a whole-genome dataset from a census-based cohort of 1,171 elderly individuals from São Paulo, Brazil, highly admixed, and unaffected by severe monogenic disorders, to investigate if pathogenic assertions in ClinVar are enriched with higher proportions of European ancestry, indicating bias. Potential loss of function (pLOF) variants were filtered from 4,250 genes associated with Mendelian disorders and annotated with ClinVar assertions. Over 1,800 single nucleotide pLOF variants were included, 381 had non-benign assertions. Among carriers (N = 463), average European ancestry was significantly higher than noncarriers (N = 708; p = .011). pLOFs in genomic contexts of non-European local ancestries were nearly three times less likely to have any ClinVar entry (OR = 0.353; p <.0001). Independent pathogenicity assertions are useful for variant classification in molecular diagnosis. However, European overrepresentation of assertions can promote distortions when classifying variants in non-European individuals, even in admixed samples with a relatively high proportion of European ancestry. The investigation and deposit of clinically relevant findings of diverse populations is fundamental improve this scenario.

Global spectrum of population-specific common missense variation in cytochrome P450 pharmacogenes

Next-generation sequencing technology has afforded the discovery of many novel variants that are of significance to inheritable pharmacogenomics (PGx) traits but a large proportion of them have unknown consequences. These include missense variants resulting in single amino acid substitutions in cytochrome P450 (CYP) proteins that can impair enzyme function, leading to altered drug efficacy and toxicity. While most unknown variants are rare, an overlooked minority are variants that are collectively rare but enriched in specific populations. Here, we analyzed sequence variation data in 141,456 individuals from across eight study populations in gnomAD for 38 CYP genes to identify such variants in addition to common variants. By further comparison with data from two PGx-specific databases (PharmVar and PharmGKB) and ClinVar, we identified 234 missense variants in 35 CYP genes, of which 107 were unknown to these databases. Most unknown variants (n = 83) were population-specific common variants and several (n = 7) were found in important CYP pharmacogenes (CYP2D6, CYP4F2, and CYP2C19). Overall, 29% (n = 31) of 107 unknown variants were predicted to affect CYP enzyme function although further biochemical characterization is necessary. These variants may elucidate part of the unexplained interpopulation differences observed in drug response.

Admixture Has Shaped Romani Genetic Diversity in Clinically Relevant Variants

Genetic patterns of inter-population variation are a result of different demographic and adaptive histories, which gradually shape the frequency distribution of the variants. However, the study of clinically relevant mutations has a Eurocentric bias. The Romani, the largest transnational minority ethnic group in Europe, originated in South Asia and received extensive gene flow from West Eurasia. Most medical genetic studies have only explored founder mutations related to Mendelian disorders in this population. Here we analyze exome sequences and genome-wide array data of 89 healthy Spanish Roma individuals to study complex traits and disease. We apply a different framework and focus on variants with both increased and decreased allele frequencies, taking into account their local ancestry. We report several OMIM traits enriched for genes with deleterious variants showing increased frequencies in Roma or in non-Roma (e.g., obesity is enriched in Roma, with an associated variant linked to South Asian ancestry; while non-insulin dependent diabetes is enriched in non-Roma Europeans). In addition, previously reported pathogenic variants also show differences among populations, where some variants segregating at low frequency in non-Roma are virtually absent in the Roma. Lastly, we describe frequency changes in drug-response variation, where many of the variants increased in Roma are clinically associated with metabolic and cardiovascular-related drugs. These results suggest that clinically relevant variation in Roma cannot only be characterized in terms of founder mutations. Instead, we observe frequency differences compared to non-Roma: some variants are absent, while other have drifted to higher frequencies. As a result of the admixture events, these clinically damaging variants can be traced back to both European and South Asian-related ancestries. This can be attributed to a different prevalence of some genetic disorders or to the fact that genetic susceptibility variants are mostly studied in populations of European descent, and can differ in individuals with different ancestries.

A cross-cohort analysis of autosomal DNA methylation sex differences in the term placenta

BACKGROUND

Human placental DNA methylation (DNAme) data is a valuable resource for studying sex differences during gestation, as DNAme profiles after delivery reflect the cumulative effects of gene expression patterns and exposures across gestation. Here, we present an analysis of sex differences in autosomal DNAme in the uncomplicated term placenta (n = 343) using the Illumina 450K array.

RESULTS

At a false discovery rate < 0.05 and a mean sex difference in DNAme beta value of > 0.10, we identified 162 autosomal CpG sites that were differentially methylated by sex and replicated in an independent cohort of samples (n = 293). Several of these differentially methylated CpG sites were part of larger correlated regions of sex differential DNAme. Although global DNAme levels did not differ by sex, the majority of significantly differentially methylated CpGs were more highly methylated in male placentae, the opposite of what is seen in differential methylation analyses of somatic tissues. Patterns of autosomal DNAme at these 162 CpGs were significantly associated with maternal age (in males) and newborn birthweight standard deviation (in females).

CONCLUSIONS

Our results provide a comprehensive analysis of sex differences in autosomal DNAme in the term human placenta. We report a list of high-confidence autosomal sex-associated differentially methylated CpGs and identify several key features of these loci that suggest their relevance to sex differences observed in normative and complicated pregnancies.

Genome-wide copy number variations in a large cohort of bantu African children

BACKGROUND

Copy number variations (CNVs) account for a substantial proportion of inter-individual genomic variation. However, a majority of genomic variation studies have focused on single-nucleotide variations (SNVs), with limited genome-wide analysis of CNVs in large cohorts, especially in populations that are under-represented in genetic studies including people of African descent.

METHODS

We carried out a genome-wide copy number analysis in > 3400 healthy Bantu Africans from Tanzania. Signal intensity data from high density (> 2.5 million probes) genotyping arrays were used for CNV calling with three algorithms including PennCNV, DNAcopy and VanillaICE. Stringent quality metrics and filtering criteria were applied to obtain high confidence CNVs.

RESULTS

We identified over 400,000 CNVs larger than 1 kilobase (kb), for an average of 120 CNVs (SE = 2.57) per individual. We detected 866 large CNVs (≥ 300 kb), some of which overlapped genomic regions previously associated with multiple congenital anomaly syndromes, including Prader-Willi/Angelman syndrome (Type1) and 22q11.2 deletion syndrome. Furthermore, several of the common CNVs seen in our cohort (≥ 5%) overlap genes previously associated with developmental disorders.

CONCLUSIONS

These findings may help refine the phenotypic outcomes and penetrance of variations affecting genes and genomic regions previously implicated in diseases. Our study provides one of the largest datasets of CNVs from individuals of African ancestry, enabling improved clinical evaluation and disease association of CNVs observed in research and clinical studies in African populations.

The influence of evolutionary history on human health and disease

Nearly all genetic variants that influence disease risk have human-specific origins; however, the systems they influence have ancient roots that often trace back to evolutionary events long before the origin of humans. Here, we review how advances in our understanding of the genetic architectures of diseases, recent human evolution and deep evolutionary history can help explain how and why humans in modern environments become ill. Human populations exhibit differences in the prevalence of many common and rare genetic diseases. These differences are largely the result of the diverse environmental, cultural, demographic and genetic histories of modern human populations. Synthesizing our growing knowledge of evolutionary history with genetic medicine, while accounting for environmental and social factors, will help to achieve the promise of personalized genomics and realize the potential hidden in an individual's DNA sequence to guide clinical decisions. In short, precision medicine is fundamentally evolutionary medicine, and integration of evolutionary perspectives into the clinic will support the realization of its full potential.

Intrinsic DNA topology as a prioritization metric in genomic fine-mapping studies

In genomic fine-mapping studies, some approaches leverage annotation data to prioritize likely functional polymorphisms. However, existing annotation resources can present challenges as many lack information for novel variants and/or may be uninformative for non-coding regions. We propose a novel annotation source, sequence-dependent DNA topology, as a prioritization metric for fine-mapping. DNA topology and function are well-intertwined, and as an intrinsic DNA property, it is readily applicable to any genomic region. Here, we constructed and applied Minor Groove Width (MGW) as a prioritization metric. Using an established MGW-prediction method, we generated a MGW census for 199 038 197 SNPs across the human genome. Summarizing a SNP's change in MGW (ΔMGW) as a Euclidean distance, ΔMGW exhibited a strongly right-skewed distribution, highlighting the infrequency of SNPs that generate dissimilar shape profiles. We hypothesized that phenotypically-associated SNPs can be prioritized by ΔMGW. We tested this hypothesis in 116 regions analyzed by a Massively Parallel Reporter Assay and observed enrichment of large ΔMGW for functional polymorphisms (P = 0.0007). To illustrate application in fine-mapping studies, we applied our MGW-prioritization approach to three non-coding regions associated with systemic lupus erythematosus. Together, this study presents the first usage of sequence-dependent DNA topology as a prioritization metric in genomic association studies.

Prevalence of disease-causing genes in Japanese patients with BRCA1/2-wildtype hereditary breast and ovarian cancer syndrome

Panel sequencing of susceptibility genes for hereditary breast and ovarian cancer (HBOC) syndrome has uncovered numerous germline variants; however, their pathogenic relevance and ethnic diversity remain unclear. Here, we examined the prevalence of germline variants among 568 Japanese patients with BRCA1/2-wildtype HBOC syndrome and a strong family history. Pathogenic or likely pathogenic variants were identified on 12 causal genes for 37 cases (6.5%), with recurrence for 4 SNVs/indels and 1 CNV. Comparisons with non-cancer east-Asian populations and European familial breast cancer cohorts revealed significant enrichment of PALB2, BARD1, and BLM mutations. Younger onset was associated with but not predictive of these mutations. Significant somatic loss-of-function alterations were confirmed on the wildtype alleles of genes with germline mutations, including PALB2 additional somatic truncations. This study highlights Japanese-associated germline mutations among patients with BRCA1/2 wildtype HBOC syndrome and a strong family history, and provides evidence for the medical care of this high-risk population.

Personalized medicine for asthma in tropical regions

PURPOSE OF REVIEW

Precision medicine could help to improve diagnosis and treatment of asthma; however, in the tropics there are special conditions to be considered for applying this strategy. In this review, we analyze recent advances of precision allergology in tropical regions, highlighting its limitations and needs in high-admixed populations living under environments with high exposure to house dust mites and helminth infections.

RECENT FINDINGS

Advances have been made regarding the genetic characterization of the great diversity of populations living in the tropics. Genes involved in shared biological pathways between immune responses to nematodes and the allergic responses suggested new mechanisms of predisposition. Genome wide association studies of asthma are progressively focusing on some highly replicated genes such as those in chromosome 17q31-13, which have been also replicated in African ancestry populations. Some diagnostic difficulties, because of the endemicity of helminth infections, are now more evident in the context of phenotype definition.

SUMMARY

The clinical impact of the advances in precision medicine for asthma in the tropics is still limited and mainly related to component resolved diagnosis. More basic and clinical research is needed to identify genetic, epigenetic, or other biologic markers that allow and accurate definition of phenotypes and endotypes of this heterogeneous disease. This will substantially improve the selection of personalized treatments.

Mixed-model admixture mapping identifies smoking-dependent loci of lung function in African Americans

Admixture mapping has led to the discovery of many genes associated with differential disease risk by ancestry, highlighting the importance of ancestry-based approaches to association studies. However, the potential of admixture mapping in deciphering the interplay between genes and environment exposures has been seldom explored. Here we performed a genome-wide screening of local ancestry-smoking interactions for five spirometric lung function phenotypes in 3300 African Americans from the COPDGene study. To account for population structure and outcome heterogeneity across exposure groups, we developed a multi-component linear mixed model for mapping gene-environment interactions and empirically showed its robustness and increased power. When applied to the COPDGene study, our approach identified two 11p15.2-3 and 2q37 loci, exhibiting local ancestry-smoking interactions at genome-wide significant level, which would have been missed by standard single-nucleotide polymorphism analyses. These two loci harbor the PARVA and RAB17 genes previously recognized to be involved in smoking behavior. Overall, our study provides the first evidence for potential synergistic effects between African ancestry and smoking on pulmonary function, and underlines the importance of ethnic diversity in genetic studies.

Evaluating the promise of inclusion of African ancestry populations in genomics

The lack of representation of diverse ancestral backgrounds in genomic research is well-known, and the resultant scientific and ethical limitations are becoming increasingly appreciated. The paucity of data on individuals with African ancestry is especially noteworthy as Africa is the birthplace of modern humans and harbors the greatest genetic diversity. It is expected that greater representation of those with African ancestry in genomic research will bring novel insights into human biology, and lead to improvements in clinical care and improved understanding of health disparities. Now that major efforts have been undertaken to address this failing, is there evidence of these anticipated advances? Here, we evaluate the promise of including diverse individuals in genomic research in the context of recent literature on individuals of African ancestry. In addition, we discuss progress and achievements on related technological challenges and diversity among scientists conducting genomic research.

Reporting of race in genome and exome sequencing studies of cancer: a scoping review of the literature

PURPOSE

Minorities are often underrepresented in clinical cancer research yet the frequency of reporting of race in genomic sequencing studies of cancer is unknown. This scoping review determines the rate at which race is reported as a demographic variable, the factors associated with reporting of race, and the participation rates of minority populations.

METHODS

PubMed was systematically searched from 1 January 2010 through 15 November 2018 and 11,014 studies were assessed for eligibility. Publications reporting genome or exome sequencing data for patients with one of the ten most common cancers in the United States were included.

RESULTS

A total of 231 publications containing sequencing data from 15,721 unique patients met inclusion criteria. Race was reported in 37% of studies compared with 84% of studies reporting age and 85% reporting gender. Reporting of race was associated with cohort size, sequencing method, familial cancer, cancers with disparities, and reporting of age and gender. Minority populations were significantly underpowered to detect recurrent pathogenic variants in most cancers.

CONCLUSION

Race is underreported as a demographic variable in genomic sequencing studies of cancer. Substantially increased efforts are needed to sequence patients from underrepresented populations to reduce health disparities in patients of non-European ancestry.

Low-frequency variants at the CYP2C9 locus among Puerto Rican patients on warfarin: in silico predictions of functionality and conservation

Aim: Perform in silico predictions of functional consequences of CYP2C9 variants identified by next-generation sequencing in Puerto Ricans. Methods: Identified low-frequency CYP2C9 variants (minor allele frequencies <2%) were evaluated using the Combined Annotation-Dependent Depletion (CADD v1.3) tools and molecular modeling/docking analysis to predict impact on CYP2C9 activity. Results: CYP2C9*5,*8,*9,*11,*12,*21 and a novel *61 induce conformational changes that affect the binding site of S-warfarin. Most of these deleterious variants occur at higher frequency among individuals with large African ancestry. Conclusion: The unfavorable distance of S-warfarin from heme group, and low-binding interactions due to these CYP2C9 variants, suggest major complications during warfarin therapy. This study contributes to the field by predicting functional alterations of rare CYP2C9 variants for the first time in Hispanics.

Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype

The human reference genome represents only a small number of individuals, which limits its usefulness for genotyping. We present a method named HISAT2 (hierarchical indexing for spliced alignment of transcripts 2) that can align both DNA and RNA sequences using a graph Ferragina Manzini index. We use HISAT2 to represent and search an expanded model of the human reference genome in which over 14.5 million genomic variants in combination with haplotypes are incorporated into the data structure used for searching and alignment. We benchmark HISAT2 using simulated and real datasets to demonstrate that our strategy of representing a population of genomes, together with a fast, memory-efficient search algorithm, provides more detailed and accurate variant analyses than other methods. We apply HISAT2 for HLA typing and DNA fingerprinting; both applications form part of the HISAT-genotype software that enables analysis of haplotype-resolved genes or genomic regions. HISAT-genotype outperforms other computational methods and matches or exceeds the performance of laboratory-based assays.

Implementation of genomics in medical practice to deliver precision medicine for an Asian population

Whilst the underlying principles of precision medicine are comparable across the globe, genomic references, health practices, costs and discrimination policies differ in Asian settings compared to the reported initiatives involving European-derived populations. We have addressed these variables by developing an evolving reference base of genomic and phenotypic data and a framework to return medically significant variants to consenting research participants applicable for the Asian context. Targeting 10,000 participants, over 2000 Singaporeans, with no known pre-existing health conditions, have consented to an extensive clinical health screen, family health history collection, genome sequencing and ongoing follow-up. Genomic variants in a subset of genes associated with Mendelian disorders and drug responses are analysed using an in-house bioinformatics pipeline. A multidisciplinary team reviews the classification of variants and a research report is generated. Medically significant variants are returned to consenting participants through a bespoke return-of-result genomics clinic. Variant validation and subsequent clinical referral are advised as appropriate. The design and implementation of this flexible learning framework enables a cohort of detailed phenotyping and genotyping of healthy Singaporeans to be established and the frequency of disease-causing variants in this population to be determined. Our findings will contribute to international precision medicine initiatives, bridging gaps with ethnic-specific data and insights from this understudied population.

Association between polygenic risk for tobacco or alcohol consumption and liability to licit and illicit substance use in young Australian adults

BACKGROUND

Co-morbid substance use is very common. Despite a historical focus using genetic epidemiology to investigate comorbid substance use and misuse, few studies have examined substance-substance associations using polygenic risk score (PRS) methods.

METHODS

Using summary statistics from the largest substance use GWAS to date (258,797- 632,802 subjects), GWAS and Sequencing Consortium of Alcohol and Nicotine use (GSCAN), we constructed PRSs for smoking initiation (PRS-SI), age of initiation of regular smoking (PRS-AI), cigarettes per day (PRS-CPD), smoking cessation (PRS-SC), and drinks per week (PRS-DPW). We then estimated the fixed effect of individual PRSs on 22 lifetime substance use and substance use disorder phenotypes collected in an independent sample of 2463 young Australian adults using genetic restricted maximal likelihood (GREML) in Genome-wide Complex Trait Analysis (GCTA), separately in females, males and both sexes together.

RESULTS

After accounting for multiple testing, PRS-SI significantly explained variation in the risk of cocaine (0.67%), amphetamine (1.54%), hallucinogens (0.72%), ecstasy (1.66%) and cannabis initiation (0.97%), as well as DSM-5 alcohol use disorder (0.72%). PRS-DPW explained 0.75%, 0.59% and 0.90% of the variation of cocaine, amphetamine and ecstasy initiation respectively. None of the 22 phenotypes including emergent classes of substance use were significantly predicted by PRS-AI, PRS-CPD, and PRS-SC.

CONCLUSIONS

To our knowledge, this is the first study to report significant genetic overlap between the polygenic risks for smoking initiation and alcohol consumption and the risk of initiating major classes of illicit substances. PRSs constructed from large discovery GWASs allows the detection of novel genetic associations.

Estimating carrier frequencies of newborn screening disorders using a whole-genome reference panel of 3552 Japanese individuals

Incidence rates of Mendelian diseases vary among ethnic groups, and frequencies of variant types of causative genes also vary among human populations. In this study, we examined to what extent we can predict population frequencies of recessive disorders from genomic data, and explored better strategies for variant interpretation and classification. We used a whole-genome reference panel from 3552 general Japanese individuals constructed by the Tohoku Medical Megabank Organization (ToMMo). Focusing on 32 genes for 17 congenital metabolic disorders included in newborn screening (NBS) in Japan, we identified reported and predicted pathogenic variants through variant annotation, interpretation, and multiple ways of classifications. The estimated carrier frequencies were compared with those from the Japanese NBS data based on 1,949,987 newborns from a previous study. The estimated carrier frequency based on genomic data with a recent guideline of variant interpretation for the PAH gene, in which defects cause hyperphenylalaninemia (HPA) and phenylketonuria (PKU), provided a closer estimate to that by the observed incidence than the other methods. In contrast, the estimated carrier frequencies for SLC25A13, which causes citrin deficiency, were much higher compared with the incidence rate. The results varied greatly among the 11 NBS diseases with single responsible genes; the possible reasons for departures from the carrier frequencies by reported incidence rates were discussed. Of note, (1) the number of pathogenic variants increases by including additional lines of evidence, (2) common variants with mild effects also contribute to the actual frequency of patients, and (3) penetrance of each variant remains unclear.

Ancestral characterization of 1018 cancer cell lines highlights disparities and reveals gene expression and mutational differences

Background

Although cell lines are an essential resource for studying cancer biology, many are of unknown ancestral origin, and their use may not be optimal for evaluating the biology of all patient populations.

Methods

An admixture analysis was performed using genome‐wide chip data from the Catalogue of Somatic Mutations in Cancer (COSMIC) Cell Lines Project to calculate genetic ancestry estimates for 1018 cancer cell lines. After stratifying the analyses by tissue and histology types, linear models were used to evaluate the influence of ancestry on gene expression and somatic mutation frequency.

Results

For the 701 cell lines with unreported ancestry, 215 were of East Asian origin, 30 were of African or African American origin, and 453 were of European origin. Notable imbalances were observed in ancestral representation across tissue type, with the majority of analyzed tissue types having few cell lines of African American ancestral origin, and with Hispanic and South Asian ancestry being almost entirely absent across all cell lines. In evaluating gene expression across these cell lines, expression levels of the genes neurobeachin line 1 (NBEAL1), solute carrier family 6 member 19 (SLC6A19), HEAT repeat containing 6 (HEATR6), and epithelial cell transforming 2 like (ECT2L) were associated with ancestry. Significant differences were also observed in the proportions of somatic mutation types across cell lines with varying ancestral proportions.

Conclusions

By estimating genetic ancestry for 1018 cancer cell lines, the authors have produced a resource that cancer researchers can use to ensure that their cell lines are ancestrally representative of the populations they intend to affect. Furthermore, the novel ancestry‐specific signal identified underscores the importance of ancestral awareness when studying cancer.

Preclinical cancer cell line research is often conducted without an awareness of ancestral background, which results in incongruities between the genetic backgrounds of used cell lines and the patient populations they are intended to represent. By calculating genetic ancestry for 1018 common cancer cell lines and identifying ancestry‐specific expression and somatic mutation patterns, the importance of ancestral awareness is emphasized, and a resource is provided that can be used by cancer researchers to ensure that their cell lines are ancestrally representative of the populations they aim to impact.

Early-onset triple-negative breast cancer in multiracial/ethnic populations: Distinct trends of prevalence of truncation mutations

Young black women are at higher risk of triple‐negative breast cancer (TNBC); however, a majority of the genetic studies on cancer predisposition were carried out in White populations. The underrepresentation of minority racial/ethnic populations in cancer genetic studies may have led to disproportionate gaps in our knowledge of cancer predisposition genes in these populations. We surveyed the protein‐truncating mutations at the exome‐wide scale and in known breast cancer predisposition genes among 170 patients of multiple racial/ethnic groups with early‐onset (≤age 50) TNBC from two independent cohorts. Black patients, on average, had a higher number of truncating mutations than Whites at the exome‐wide level, but fewer truncating mutations in the panel of known breast cancer genes. White TNBC patients showed a strong enrichment of truncating variants in known breast cancer genes, whereas no such enrichment was found among Black patients. Our findings indicate likely more breast cancer disposition genes yet to be discovered in minority racial/ethnic groups, and the current multigene panels may result in unequal benefits from cancer genetic testing.

A locus on chromosome 5 shows African ancestry-limited association with alloimmunization in sickle cell disease

Red blood cell (RBC) transfusion remains a critical therapeutic intervention in sickle cell disease (SCD); however, the apparent propensity of some patients to regularly develop RBC alloantibodies after transfusion presents a significant challenge to finding compatible blood for so-called alloimmunization responders. Predisposing genetic loci have long been thought to contribute to the responder phenomenon, but to date, no definitive loci have been identified. We undertook a genome-wide association study of alloimmunization responder status in 267 SCD multiple transfusion recipients, using genetic estimates of ancestral admixture to bolster our findings. Analyses revealed single nucleotide polymorphisms (SNPs) on chromosomes 2 and 5 approaching genome-wide significance (minimum P = 2.0 × 10-8 and 8.4 × 10-8, respectively), with local ancestry analysis demonstrating similar levels of admixture in responders and nonresponders at implicated loci. Association at chromosome 5 was nominally replicated in an independent cohort of 130 SCD transfusion recipients, with meta-analysis surpassing genome-wide significance (rs75853687, P meta = 6.6 × 10-9), and this extended to individuals forming multiple (>3) alloantibodies (P meta = 9.4 × 10-5). The associated variant is rare outside of African populations, and orthogonal genome-wide haplotype analyses, contingent on local ancestry, revealed genome-wide significant sharing of a ∼60-kb haplotype of African ancestry at the chromosome 5 locus (Bayes Factor = 4.95). This locus overlaps a putative cis-acting enhancer predicted to regulate transcription of ADRA1B and the lncRNA LINC01847, both members of larger ontologies associated with immune regulation. Our findings provide potential insights to the pathophysiology underlying the development of alloantibodies and implicate non-RBC ancestry-limited loci in the susceptibility to alloimmunization.

Single nucleotide polymorphisms in the MYLKP1 pseudogene are associated with increased colon cancer risk in African Americans

INTRODUCTION

Pseudogenes are paralogues of functional genes historically viewed as defunct due to either the lack of regulatory elements or the presence of frameshift mutations. Recent evidence, however, suggests that pseudogenes may regulate gene expression, although the functional role of pseudogenes remains largely unknown. We previously reported that MYLKP1, the pseudogene of MYLK that encodes myosin light chain kinase (MLCK), is highly expressed in lung and colon cancer cell lines and tissues but not in normal lung or colon. The MYLKP1 promoter is minimally active in normal bronchial epithelial cells but highly active in lung adenocarcinoma cells. In this study, we further validate MYLKP1 as an oncogene via elucidation of the functional role of MYLKP1 genetic variants in colon cancer risk.

METHODS

Proliferation and migration assays were performed in MYLKP1-transfected colon and lung cancer cell lines (H441, A549) and commercially-available normal lung and colon cells. Fourteen MYLKP1 SNPs (MAFs >0.01) residing within the 4 kb MYLKP1 promoter region, the core 1.4 kb of MYLKP1 gene, and a 4 kb enhancer region were selected and genotyped in a colorectal cancer cohort. MYLKP1 SNP influences on activity of MYLKP1 promoter (2kb) was assessed by dual luciferase reporter assay.

RESULTS

Cancer cell lines, H441 and A549, exhibited increased MYLKP1 expression, increased MYLKP1 luciferase promoter activity, increased proliferation and migration. Genotyping studies identified two MYLKP1 SNPs (rs12490683; rs12497343) that significantly increase risk of colon cancer in African Americans compared to African American controls. Rs12490683 and rs12497343 further increase MYLKP1 promoter activity compared to the wild type MYLKP1 promoter.

CONCLUSION

MYLKP1 is a cancer-promoting pseudogene whose genetic variants differentially enhance cancer risk in African American populations.

Evolutionary genomic dynamics of Peruvians before, during, and after the Inca Empire

Through the Peruvian Genome Project we generate and analyze the genomes of 280 individuals where the majority have >90% Native American ancestry and explore questions at the interface of evolutionary genetics, history, anthropology, and medicine. This is the most extensive sampling of high-coverage Native American and mestizo whole genomes to date. We estimate an initial peopling of Peru was rapid and began by 12,000 y ago. In addition, the mestizo populations exhibit admixture between Native American groups prior to their Spanish admixture and was likely influenced by the Inca Empire and Spanish conquest. Our results address important Native American population history questions and establish a dataset beneficial to address the underrepresentation of Native American ancestry in sequencing studies.

Native Americans from the Amazon, Andes, and coastal geographic regions of South America have a rich cultural heritage but are genetically understudied, therefore leading to gaps in our knowledge of their genomic architecture and demographic history. In this study, we sequence 150 genomes to high coverage combined with an additional 130 genotype array samples from Native American and mestizo populations in Peru. The majority of our samples possess greater than 90% Native American ancestry, which makes this the most extensive Native American sequencing project to date. Demographic modeling reveals that the peopling of Peru began ∼12,000 y ago, consistent with the hypothesis of the rapid peopling of the Americas and Peruvian archeological data. We find that the Native American populations possess distinct ancestral divisions, whereas the mestizo groups were admixtures of multiple Native American communities that occurred before and during the Inca Empire and Spanish rule. In addition, the mestizo communities also show Spanish introgression largely following Peruvian Independence, nearly 300 y after Spain conquered Peru. Further, we estimate migration events between Peruvian populations from all three geographic regions with the majority of between-region migration moving from the high Andes to the low-altitude Amazon and coast. As such, we present a detailed model of the evolutionary dynamics which impacted the genomes of modern-day Peruvians and a Native American ancestry dataset that will serve as a beneficial resource to addressing the underrepresentation of Native American ancestry in sequencing studies.

Whole-Exome Sequencing Reveals Uncaptured Variation and Distinct Ancestry in the Southern African Population of Botswana

Large-scale, population-based genomic studies have provided a context for modern medical genetics. Among such studies, however, African populations have remained relatively underrepresented. The breadth of genetic diversity across the African continent argues for an exploration of local genomic context to facilitate burgeoning disease mapping studies in Africa. We sought to characterize genetic variation and to assess population substructure within a cohort of HIV-positive children from Botswana-a Southern African country that is regionally underrepresented in genomic databases. Using whole-exome sequencing data from 164 Batswana and comparisons with 150 similarly sequenced HIV-positive Ugandan children, we found that 13%-25% of variation observed among Batswana was not captured by public databases. Uncaptured variants were significantly enriched (p = 2.2 × 10^-16) for coding variants with minor allele frequencies between 1% and 5% and included predicted-damaging non-synonymous variants. Among variants found in public databases, corresponding allele frequencies varied widely, with Botswana having significantly higher allele frequencies among rare (<1%) pathogenic and damaging variants. Batswana clustered with other Southern African populations, but distinctly from 1000 Genomes African populations, and had limited evidence for admixture with extra-continental ancestries. We also observed a surprising lack of genetic substructure in Botswana, despite multiple tribal ethnicities and language groups, alongside a higher degree of relatedness than purported founder populations from the 1000 Genomes project. Our observations reveal a complex, but distinct, ancestral history and genomic architecture among Batswana and suggest that disease mapping within similar Southern African populations will require a deeper repository of genetic variation and allelic dependencies than presently exists.

An American Thoracic Society/National Heart, Lung, and Blood Institute Workshop Report: Addressing Respiratory Health Equality in the United States

Health disparities related to race, ethnicity, and socioeconomic status persist and are commonly encountered by practitioners of pediatric and adult pulmonary, critical care, and sleep medicine in the United States. To address such disparities and thus progress toward equality in respiratory health, the American Thoracic Society and the National Heart, Lung, and Blood Institute convened a workshop in May of 2015. The workshop participants addressed health disparities by focusing on six topics, each of which concluded with a panel discussion that proposed recommendations for research on racial, ethnic, and socioeconomic disparities in pulmonary, critical care, and sleep medicine. Such recommendations address best practices to advance research on respiratory health disparities (e.g., characterize broad ethnic groups into subgroups known to differ with regard to a disease of interest), risk factors for respiratory health disparities (e.g., study the impact of new tobacco or nicotine products on respiratory diseases in minority populations), addressing equity in access to healthcare and quality of care (e.g., conduct longitudinal studies of the impact of the Affordable Care Act on respiratory and sleep disorders), the impact of personalized medicine on disparities research (e.g., implement large studies of pharmacogenetics in minority populations), improving design and methodology for research studies in respiratory health disparities (e.g., use study designs that reduce participants' burden and foster trust by engaging participants as decision-makers), and achieving equity in the pulmonary, critical care, and sleep medicine workforce (e.g., develop and maintain robust mentoring programs for junior faculty, including local and external mentors). Addressing these research needs should advance efforts to reduce, and potentially eliminate, respiratory, sleep, and critical care disparities in the United States.

Linking Race, Cancer Outcomes, and Tissue Repair

The burden of cancer in the United States is unevenly spread across its different populations, with stark differences in both disease prevalence and outcome on the basis of race and ethnicity. Although a large portion of these differences can be explained by a variety of sociobehavioral and socioeconomic factors, even after these exposures are taken into consideration, considerable disparities persist. In this review, we explore a conceptual framework of biological theories and unifying concepts, based on an evolutionary perspective, that may help better define common guiding principles for exploration of underlying causes of cancer health disparities. The ultimate goal of this conceptual perspective is to outline approaches that may aid in establishing integrated pathway and processes analyses to provide useful insights to guide the development of future interventions. These interventions will improve outcome, increase prevention, and ultimately eliminate all disparities.

Distinctive DNA mismatch repair and APC rare variants in African Americans with colorectal neoplasia

PURPOSE

African Americans have a higher incidence and mortality from colorectal cancer. This disparity might be due, in part, to the type of mutations in driver genes. In this study, we examined alterations specific to APC, MSH3, and MSH6 genes using targeted exome sequencing to determine distinctive variants in the course of neoplastic transformation.

EXPERIMENTAL DESIGN

A total of 140 African American colon samples (30 normal, 21 adenomas, 33 advanced adenomas and 56 cancers) were used as our discovery set on an Ion Torrent platform. A 36 samples subset was resequenced on an Illumina platform for variants' validation. Bioinformatics analyses were performed and novel validated variants are reported.

RESULTS

Two novel MSH6 variants were validated and mapped to the MutS-V region near the MSH2 binding site. For MSH3, 4 known variants were validated and were located in exon 10 (3 non-synonymous) and exon 18 (1 synonymous). As for APC, 20 variants were validated with 4 novel variants: 3 stopgain and 1 non-synonymous. These variants mapped prior to and on the Armadillo repeats region, to the 15-amino acid repeat region, and to the 20-amino acid repeats region, respectively.

CONCLUSION

We defined novel variants that target DNA mismatch repair and APC genes in African Americans with colorectal lesions. A greater frequency of variants in genes encoding DNA mismatch repair functions and APC likely plays major roles in colorectal cancer initiation and higher incidence of the disease in African Americans.

Personalized medicine and Hispanic health: improving health outcomes and reducing health disparities - a National Heart, Lung, and Blood Institute workshop report

Persons of Hispanic/Latino descent may represent different ancestries, ethnic and cultural groups and countries of birth. In the U.S., the Hispanic/Latino population is projected to constitute 29% of the population by 2060. A personalized approach focusing on individual variability in genetics, environment, lifestyle and socioeconomic determinants of health may advance the understanding of some of the major factors contributing to the health disparities experienced by Hispanics/Latinos and other groups in the U.S., thus leading to new strategies that improve health care outcomes. However, there are major gaps in our current knowledge about how personalized medicine can shape health outcomes among Hispanics/Latinos and address the potential factors that may explain the observed differences within this heterogeneous group, and between this group and other U.S. demographic groups. For that purpose, the National Heart, Lung, and Blood Institute (NHLBI), in collaboration with the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), and the Food and Drug Administration (FDA), held a workshop in which experts discussed (1) potential approaches to study medical treatments and health outcomes among Hispanics/Latinos and garner the necessary evidence to fill gaps of efficacy, effectiveness and safety of therapies for heart, lung, blood and sleep (HLBS) disorders and conditions--and their risk factors; (2) research opportunities related to personalized medicine to improve knowledge and develop effective interventions to reduce health disparities among Hispanics/Latinos in the U.S.; and (3) the incorporation of expanded sociocultural and socioeconomic data collection and genetic/genomic/epigenetic information of Hispanic/Latino patients into their clinical assessments, to account for individual variability in ancestry; physiology or disease risk; culture; environment; lifestyle; and socioeconomic determinants of health. The experts also provided recommendations on: sources of Hispanic/Latino health data and strategies to enhance its collection; policy; genetics, genomics and epigenetics research; and integrating Hispanic/Latino health research within clinical settings.