Variations in the genomic profiles and clinical behavior of meningioma by racial and ethnic group.

OBJECTIVE: The influence of socioeconomic factors on racial disparities among patients with sporadic meningiomas is well established, yet other potential causative factors warrant further exploration. The authors of this study aimed to determine whether there is significant variation in the genomic profile of meningiomas among patients of different races and ethnicities and its correlation with clinical outcomes. METHODS: The demographic, genomic, and clinical data of patients aged 18 years and older who had undergone surgery for sporadic meningioma between September 2008 and November 2021 were analyzed. Statistical analyses were performed to detect differences across all racial/ethnic groups, as were direct comparisons between Black and non-Black groups plus Hispanic and non-Hispanic groups. RESULTS: This study included 460 patients with intracranial meningioma. Hispanic patients were significantly younger at surgery (53.9 vs 60.2 years, p = 0.0006) and more likely to show symptoms. Black patients had a higher incidence of anterior skull base tumors (OR 3.2, 95% CI 1.7-6.3, p = 0.0008) and somatic hedgehog mutations (OR 5.3, 95% CI 1.6-16.6, p = 0.003). Hispanics were less likely to exhibit the aggressive genomic characteristic of chromosome 1p deletion (OR 0.28, 95% CI 0.07-1.2, p = 0.06) and displayed higher rates of TRAF7 somatic driver mutations (OR 2.96 95% CI 1.1-7.8, p = 0.036). Black patients had higher rates of recurrence (OR 2.6, 95% CI 1.3-5.2, p = 0.009) and shorter progression-free survival (PFS; HR 2.9, 95% CI 1.6-5.4, p = 0.002) despite extents of resection (EORs) similar to those of non-Black patients (p = 0.745). No significant differences in overall survival were observed among groups. CONCLUSIONS: Despite similar EORs, Black patients had worse clinical outcomes following meningioma resection, characterized by a higher prevalence of somatic hedgehog mutations, increased recurrence rates, and shorter PFS. Meanwhile, Hispanic patients had less aggressive meningiomas, a predisposition for TRAF7 mutations, and no difference in PFS. These findings could inform the care and treatment strategies for meningiomas, and they establish the foundation for future studies focusing on the genomic origins of these observed differences.

SNVstory: inferring genetic ancestry from genome sequencing data.

BACKGROUND: Genetic ancestry, inferred from genomic data, is a quantifiable biological parameter. While much of the human genome is identical across populations, it is estimated that as much as 0.4% of the genome can differ due to ancestry. This variation is primarily characterized by single nucleotide variants (SNVs), which are often unique to specific genetic populations. Knowledge of a patient's genetic ancestry can inform clinical decisions, from genetic testing and health screenings to medication dosages, based on ancestral disease predispositions. Nevertheless, the current reliance on self-reported ancestry can introduce subjectivity and exacerbate health disparities. While genomic sequencing data enables objective determination of a patient's genetic ancestry, existing approaches are limited to ancestry inference at the continental level. RESULTS: To address this challenge, and create an objective, measurable metric of genetic ancestry we present SNVstory, a method built upon three independent machine learning models for accurately inferring the sub-continental ancestry of individuals. We also introduce a novel method for simulating individual samples from aggregate allele frequencies from known populations. SNVstory includes a feature-importance scheme, unique among open-source ancestral tools, which allows the user to track the ancestral signal broadcast by a given gene or locus. We successfully evaluated SNVstory using a clinical exome sequencing dataset, comparing self-reported ethnicity and race to our inferred genetic ancestry, and demonstrate the capability of the algorithm to estimate ancestry from 36 different populations with high accuracy. CONCLUSIONS: SNVstory represents a significant advance in methods to assign genetic ancestry, opening the door to ancestry-informed care. SNVstory, an open-source model, is packaged as a Docker container for enhanced reliability and interoperability. It can be accessed from https://github.com/nch-igm/snvstory .

Genetic and environmental influence on alcohol intent and alcohol sips among U.S. children-Effects across sex, race, and ethnicity.

INTRODUCTION: Alcohol intent (the susceptibility to initiating alcohol use) and alcohol sips (the initiation of alcohol) in youth are a multifactorial puzzle with many components. This research aims to examine the connection between genetic and environmental factors across sex, race and ethnicity. METHODS: Data was obtained from the twin hub of the Adolescent Brain Cognitive Development (ABCD) study at baseline (2016-2018). Variance component models were conducted to dissect the additive genetic (A), common (C) and unique environmental (E) effects on alcohol traits. The proportion of the total alcohol phenotypic variation attributable to additive genetic factors is reported as heritability (h2). RESULTS: The sample (n = 1,772) included an approximately equal male-female distribution. The 886 same-sex twin pairs were 60.4% dizygotic (DZ), 39.6% monozygotic (MZ), 65.4% non-Hispanic Whites, 13.9% non-Hispanic Blacks, 10.8% of Hispanics with a mean age of 121.2 months. Overall, genetic predisposition was moderate for alcohol intent (h2 = 28%, p = .006) and low for alcohol initiation (h2 = 4%, p = 0.83). Hispanics (h2 = 53%, p < .0001) and Blacks (h2 = 48%, p < .0001) demonstrated higher alcohol intent due to additive genetic factors than Whites (h2 = 34%, p < .0001). Common environmental factors explained more variation in alcohol sips in females (c2 = 63%, p = .001) than in males (c2 = 55%, p = .003). Unique environmental factors largely attributed to alcohol intent, while common environmental factors explained the substantial variation in alcohol initiation. CONCLUSION: Sex and racial/ethnic disparities in genetic and environmental risk factors for susceptibility to alcohol initiation can lead to significant health disparities. Certain populations may be at greater risk for alcohol use due to their genetic and ecological factors at an early age.

Ancestry, race and ethnicity: the role and relevance of language in clinical genetics practice.

BACKGROUND: The terms ancestry, race and ethnicity are used variably within the medical literature and within society and clinical care. Biological lineage can provide an important context for the interpretation of genomic data, but the language used, and practices around when to ascertain this, vary. METHODS: Using a fictional case scenario we explore the relevance of questions around ancestry, race and ethnicity in clinical genetic practice. RESULTS: In the UK, data on 'ethnicity' are routinely collected by those using genomic medicine, as well as within the wider UK National Health Service, although the reasons for this are not always clear to practitioners and patients. Sometimes it is requested as a proxy for biological lineage to aid variant interpretation, refine estimations of carrier frequency and guide decisions around the need for pharmacogenetic testing. CONCLUSION: There are many challenges around the use and utility of these terms. Currently, genomic databases are populated primarily with data from people of European descent, and this can lead to health disparities and poorer service for minoritised or underserved populations. Sensitivity and consideration are needed when communicating with patients around these areas. We explore the role and relevance of language around biological lineage in clinical genetics practice.

Population Pharmacogenomics for Health Equity.

Health equity means the opportunity for all people and populations to attain optimal health, and it requires intentional efforts to promote fairness in patient treatments and outcomes. Pharmacogenomic variants are genetic differences associated with how patients respond to medications, and their presence can inform treatment decisions. In this perspective, we contend that the study of pharmacogenomic variation within and between human populations-population pharmacogenomics-can and should be leveraged in support of health equity. The key observation in support of this contention is that racial and ethnic groups exhibit pronounced differences in the frequencies of numerous pharmacogenomic variants, with direct implications for clinical practice. The use of race and ethnicity to stratify pharmacogenomic risk provides a means to avoid potential harm caused by biases introduced when treatment regimens do not consider genetic differences between population groups, particularly when majority group genetic profiles are assumed to hold for minority groups. We focus on the mitigation of adverse drug reactions as an area where population pharmacogenomics can have a direct and immediate impact on public health.

Human microbiome variation associated with race and ethnicity emerges as early as 3 months of age.

Human microbiome variation is linked to the incidence, prevalence, and mortality of many diseases and associates with race and ethnicity in the United States. However, the age at which microbiome variability emerges between these groups remains a central gap in knowledge. Here, we identify that gut microbiome variation associated with race and ethnicity arises after 3 months of age and persists through childhood. One-third of the bacterial taxa that vary across caregiver-identified racial categories in children are taxa reported to also vary between adults. Machine learning modeling of childhood microbiomes from 8 cohort studies (2,756 samples from 729 children) distinguishes racial and ethnic categories with 87% accuracy. Importantly, predictive genera are also among the top 30 most important taxa when childhood microbiomes are used to predict adult self-identified race and ethnicity. Our results highlight a critical developmental window at or shortly after 3 months of age when social and environmental factors drive race and ethnicity-associated microbiome variation and may contribute to adult health and health disparities.

Beyond borders: A commentary on the benefit of promoting immigrant populations in genome-wide association studies.

Immigrants are an important part of many high-income nations, in that they contribute to the sociocultural tapestry, economic well-being, and demographic diversity of their receiving countries and communities. Yet, genomic studies to date have generally focused on non-immigrant, European-ancestry populations. Although this approach has proven fruitful in discovering and validating genomic loci, within the context of racially/ethnically diverse countries like the United States-wherein half of immigrants hail from Latin America and another quarter from Asia-this approach is insufficient. There is a persistent diversity gap in genomic research in terms of both current samples and genome-wide association studies, meaning that the field's understanding of genetic architecture and gene-environmental interactions is being hampered. In this commentary, I provide motivating examples of recent research developments related to the following: (1) how the increased ancestral diversity, such as seen among Latin American immigrants, improves power to discover and document genomic loci, (2) informs how environmental factors, such as immigration-related exposures, interact with genotypes to influence phenotypes, and (3) how inclusion can be promoted through community-engaged research programs and policies. I conclude that greater inclusion of immigrants in genomic research can move the field forward toward novel discoveries and interventions to address racial/ethnic health disparities.

Abandoning the word Caucasian.

Traditionally, the field of genetics has used patient-reported genetic ancestry to assist in risk assessment, calculate detection rates, and understand residual risks for recessive or X-linked genetic diseases. Patient-reported genetic ancestry is useful for variant curation, based on practice guidelines from medical societies. Words used to describe a person's race, ethnicity, and genetic ancestry have changed over the last few centuries, especially in the last few decades. The origin and use of Caucasian to describe people of European ancestry have come into question. With recommendations from the Department of Health and Human Services (HHS) and the American College of Medical Genetics and Genomics (ACMG), among other organizations, the medical and genetics communities are moving away from using this term altogether. The purpose of this article is to review the history of the word Caucasian and to provide evidence that it should be avoided when documenting genetic ancestry in medical records, laboratory forms, and medical research.

Residential Locale Is Associated with Disparities in Genetic Testing-Related Outcomes Among BRCA1/2-Positive Women.

BACKGROUND: While research on hereditary genetic testing for BRCA1/2 mutations continues to emerge, there remain unanswered questions regarding access to testing and cancer-related care. Our study determined the associations between race/ethnicity, residential locale, and genetic testing provider and related outcomes among US women with BRCA1/2 genetic mutations. METHODS: One hundred ninety-three BRCA1/2-positive women from vulnerable health backgrounds were recruited via private national Facebook BRCA1/2-oriented support groups and completed an online survey. Adjusted odds ratios (aOR) and 95% confidence intervals (CIs) were estimated using multivariable logistic regression for the associations between race/ethnicity, residential locale, and genetic testing-related outcomes. RESULTS: Women ranged in age (18-75, M = 39.5, SD = 10.7), and most were non-Hispanic white (66.3%) and lived in a suburban locale (54.9%). Women living in suburban areas were significantly less likely (aOR, .369, 95% CI, .177-.771) to receive behavioral referrals after genetic testing compared to those living in an urban locale. Women living in rural areas and suburban areas were 4.72 times more likely (95% CI, 1.48-15.1, p = .009) and 2.61 times more likely (95% CI, 1.05-6.48, p = .038), respectively, to receive genetic testing from a primary care provider versus private genetic testing office/hospital compared to women in urban locales. Associations between race/ethnicity and genetic testing outcomes were not statistically significant. Residential locale did not predict the odds of undergoing surgery for risk reduction or surveillance for early detection. CONCLUSION: Our study identifies disparities in genetic testing resources among women living in suburban and rural areas. These findings can be used to inform future care, research, and community resources that may impact services relating to genetic testing within these locales.

Is there a way to reduce the inequity in variant interpretation on the basis of ancestry?

The underrepresentation of non-European ancestry groups in current genomic databases complicates interpretation of their genetic test results, yielding a much higher prevalence of variants of uncertain significance (VUSs). Such VUS findings can frustrate the goals of genetic testing, create anxiety in patients, and lead to unnecessary medical interventions. Approaches to addressing underrepresentation of people with genetic ancestries other than European are being undertaken by broad-based recruitment efforts. However, some underrepresented groups have concerns that might preclude participation in such efforts. We describe here two initiatives aimed at meeting the needs of underrepresented ancestry groups in genomic datasets. The two communities, the Sephardi Jewish community in New York and First Peoples of Canada, have very different concerns about contributing to genomic research and datasets. Sephardi concerns focus on the possible negative effects of genetic findings on the marriage prospects of family members. Canadian Indigenous populations seek control over the research uses to which their genetic data would be put. Both cases involve targeted efforts to respond to the groups' concerns; these efforts include governance models aimed at ensuring that the data are used primarily to inform clinical test analyses and at achieving successful engagement and participation of community members. We suggest that these initiatives could provide models for other ancestral groups seeking to improve the accuracy and utility of clinical genetic testing while respecting the underlying preferences and values of community members with regard to the use of their genetic data.

Effects of genetic ancestry and socioeconomic deprivation on ethnic differences in serum creatinine.

The inclusion of ethnicity in equations for estimating the glomerular filtration rate (eGFR) from serum creatinine levels has been challenged since ethnicity is socially defined and therefore a poor proxy for biological differences. We hypothesized that genetic ancestry (GA) would be more strongly associated with creatinine levels among healthy individuals than self-identified ethnicity. We studied a diverse cohort of 35,590 participants characterized as part of the UK Biobank, grouped by self-reported ethnicity: Black, East Asian, Mixed, Other, South Asian, and White. We used multivariable modeling to test for associations between ethnicity, GA, socioeconomic deprivation, and serum creatinine levels, including covariates for age, sex, height, and body mass index. Model fit comparisons and relative importance analysis were used to compare the effects of ethnicity and GA on creatinine levels. Black ethnicity shows a positive effect on participant serum creatinine levels (ß = 9.36 ± 0.38), whereas East Asian (ß = -1.80 ± 0.66) and South Asian (ß = -0.28 ± 0.36) ethnicity show negative effects on creatinine. Male sex (ß = 17.69 ± 0.34) and height (ß = 0.13 ± 0.02) also show high positive associations with creatinine levels, while socioeconomic deprivation (ß = -0.04 ± 0.04) shows no significant association. African ancestry has the highest association (ß = 13.81 ± 0.52) with creatinine levels. Overall, GA (9.06%) explains significantly more of the variation in creatinine levels than ethnicity (4.96%), with African ancestry (6.36%) alone explaining more of the variation than ethnicity. We found that GA explains more of the variation in serum creatinine levels than socioeconomic deprivation, suggesting the possibility that ethnic differences in creatinine are shaped by genetic rather than social factors.

Race/ethnicity-associated blood DNA methylation differences between Japanese and European American women: an exploratory study.

BACKGROUND: Racial/ethnic disparities in health reflect a combination of genetic and environmental causes, and DNA methylation may be an important mediator. We compared in an exploratory manner the blood DNA methylome of Japanese Americans (JPA) versus European Americans (EUA). METHODS: Genome-wide buffy coat DNA methylation was profiled among healthy Multiethnic Cohort participant women who were Japanese (JPA; n = 30) or European (EUA; n = 28) Americans aged 60-65. Differentially methylated CpGs by race/ethnicity (DM-CpGs) were identified by linear regression (Bonferroni-corrected P < 0.1) and analyzed in relation to corresponding gene expression, a priori selected single nucleotide polymorphisms (SNPs), and blood biomarkers of inflammation and metabolism using Pearson or Spearman correlations (FDR < 0.1). RESULTS: We identified 174 DM-CpGs with the majority of hypermethylated in JPA compared to EUA (n = 133), often in promoter regions (n = 48). Half (51%) of the genes corresponding to the DM-CpGs were involved in liver function and liver disease, and the methylation in nine genes was significantly correlated with gene expression for DM-CpGs. A total of 156 DM-CpGs were associated with rs7489665 (SH2B1). Methylation of DM-CpGs was correlated with blood levels of the cytokine MIP1B (n = 146). We confirmed some of the DM-CpGs in the TCGA adjacent non-tumor liver tissue of Asians versus EUA. CONCLUSION: We found a number of differentially methylated CpGs in blood DNA between JPA and EUA women with a potential link to liver disease, specific SNPs, and systemic inflammation. These findings may support further research on the role of DNA methylation in mediating some of the higher risk of liver disease among JPA.

Excess mortality from COVID and non-COVID causes in minority populations.

The 2020 US mortality totaled 2.8 million after early March, which is 17.3% higher than age-population-weighted mortality over the same time interval in 2017 to 2019, for a total excess death count of 413,592. We use data on weekly death counts by cause, as well as life tables, to quantify excess mortality and life years lost from both COVID-19 and non-COVID-19 causes by race/ethnicity, age, and gender/sex. Excess mortality from non-COVID-19 causes is substantial and much more heavily concentrated among males and minorities, especially Black, non-Hispanic males, than COVID-19 deaths. Thirty-four percent of the excess life years lost for males is from non-COVID-19 causes. While minorities represent 36% of COVID-19 deaths, they represent 70% of non-COVID-19 related excess deaths and 58% of non-COVID-19 excess life years lost. Black, non-Hispanic males represent only 6.9% of the population, but they are responsible for 8.9% of COVID-19 deaths and 28% of 2020 excess deaths from non-COVID-19 causes. For this group, nearly half of the excess life years lost in 2020 are due to non-COVID-19 causes.

Assessment of the effectiveness of the EUROFORGEN NAME and Precision ID Ancestry panel markers for ancestry investigations.

The EUROFORGEN NAME panel is a regional ancestry panel designed to differentiate individuals from the Middle East, North Africa, and Europe. The first version of the panel was developed for the MassARRAY system and included 111 SNPs. Here, a custom AmpliSeq EUROFORGEN NAME panel with 102 of the original 111 loci was used to sequence 1098 individuals from 14 populations from Europe, the Middle East, North Africa, North-East Africa, and South-Central Asia. These samples were also sequenced with a global ancestry panel, the Precision ID Ancestry Panel. The GenoGeographer software was used to assign the AIM profiles to reference populations and calculate the weight of the evidence as likelihood ratios. The combination of the EUROFORGEN NAME and Precision ID Ancestry panels led to fewer ambiguous assignments, especially for individuals from the Middle East and South-Central Asia. The likelihood ratios showed that North African individuals could be separated from European and Middle Eastern individuals using the Precision ID Ancestry Panel. The separation improved with the addition of the EUROFORGEN NAME panel. The analyses also showed that the separation of Middle Eastern populations from European and South-Central Asian populations was challenging even when both panels were applied.

The impact of socioeconomic and phenotypic traits on self-perception of ethnicity in Latin America.

Self-perception of ethnicity is a complex social trait shaped by both, biological and non-biological factors. We developed a comprehensive analysis of ethnic self-perception (ESP) on a large sample of Latin American mestizos from five countries, differing in age, socio-economic and education context, external phenotypic attributes and genetic background. We measured the correlation of ESP against genomic ancestry, and the influence of physical appearance, socio-economic context, and education on the distortion observed between both. Here we show that genomic ancestry is correlated to aspects of physical appearance, which in turn affect the individual ethnic self-perceived ancestry. Also, we observe that, besides the significant correlation among genomic ancestry and ESP, specific physical or socio-economic attributes have a strong impact on self-perception. In addition, the distortion among ESP and genomic ancestry differs across age ranks/countries, probably suggesting the underlying effect of past public policies regarding identity. Our results indicate that individuals' own ideas about its origins should be taken with caution, especially in aspects of modern life, including access to work, social policies, and public health key decisions such as drug administration, therapy design, and clinical trials, among others.

Evidence of the interplay of genetics and culture in Ethiopia.

The rich linguistic, ethnic and cultural diversity of Ethiopia provides an unprecedented opportunity to understand the level to which cultural factors correlate with-and shape-genetic structure in human populations. Using primarily new genetic variation data covering 1,214 Ethiopians representing 68 different ethnic groups, together with information on individuals' birthplaces, linguistic/religious practices and 31 cultural practices, we disentangle the effects of geographic distance, elevation, and social factors on the genetic structure of Ethiopians today. We provide evidence of associations between social behaviours and genetic differences among present-day peoples. We show that genetic similarity is broadly associated with linguistic affiliation, but also identify pronounced genetic similarity among groups from disparate language classifications that may in part be attributable to recent intermixing. We also illustrate how groups reporting the same culture traits are more genetically similar on average and show evidence of recent intermixing, suggesting that shared cultural traits may promote admixture. In addition to providing insights into the genetic structure and history of Ethiopia, we identify the most important cultural and geographic predictors of genetic differentiation and provide a resource for designing sampling protocols for future genetic studies involving Ethiopians.

Geographical and linguistic structure in the people of Kenya demonstrated using 21 autosomal STRs.

Kenya is a diverse and populous nation that employs DNA evidence in its criminal justice system, and therefore requires reliable information on autosomal STR allele frequency variation across the country and in its many ethnic groups. In order to provide reference data and to assess population structure, we analysed the 21 autosomal STRs in the GlobalFiler multiplex in a sample of 510 indigenous Kenyans representing the country's eight former provinces, 43 of its 47 counties, three main linguistic families and all 29 ethnic groups that each comprise >0.5% of the 2019 census population. The indigenous population originated from successive migrations of Cushitic, Nilotic and Bantu speaking groups who settled in regions that suited their distinctive sustenance lifestyles. Consequently, they now largely reside in a patchwork of communities with strong associations with particular counties and provinces and limited degrees of inter-group marriage, as shown by DNA donors' ancestry details. We found significant genetic differentiation between the three Nilotic language sub-families, with Western Nilotes (the Luo ethnic group) showing greater similarity to the Bantu than the Southern and Eastern Nilotes which themselves showed closer affinity to the Cushitic speakers. This concurs with previous genetic, linguistic and social studies. Comparisons with other African populations also showed that linguistic affiliation is a stronger factor than geography. This study revealed several rare off-ladder alleles whose structure was determined by Sanger sequencing. Among the unusual features that could affect profile interpretation were a deletion of Amelogenin Y but no other forensic marker (autosomal or Y-chromosomal), a triallelic pattern at TPOX and an extremely short SE33 allele falling within the expected size range of D7S820. Compared with the currently implemented Identifiler multiplex, Random Match Probabilities decreased from 6.4 × 10-19 to 3.9 × 10-27. The appreciation of local population structure provided by the geographically and ethnically representative sample in this study highlights the structured genetic landscape of Kenya.