Ancestral Background Research Articles

Exploring the Relationships Between Autozygosity, Educational Attainment, and Cognitive Ability in a Contemporary, Trans-Ancestral American Sample.

Previous studies have found significant associations between estimated autozygosity - the proportion of an individual's genome contained in homozygous segments due to distant inbreeding - and multiple traits, including educational attainment (EA) and cognitive ability. In one study, estimated autozygosity showed a stronger association with parental EA than the subject's own EA. This was likely driven by parental EA's association with mobility: more educated parents tended to migrate further from their hometown, and because of the strong correlation between ancestry and geography in the Netherlands, these individuals chose partners farther from their ancestry and therefore more different from them genetically. We examined the associations between estimated autozygosity, cognitive ability, and parental EA in a contemporary sub-sample of adolescents from the Adolescent Brain Cognitive Development Study℠ (ABCD Study®) (analytic N = 6,504). We found a negative association between autozygosity and child cognitive ability consistent with previous studies, while the associations between autozygosity and parental EA were in the expected direction of effect (with greater levels of autozygosity being associated with lower EA) but the effect sizes were significantly weaker than those estimated in previous work. We also found a lower mean level of autozygosity in the ABCD sample compared to previous autozygosity studies, which may reflect overall decreasing levels of autozygosity over generations. Variation in spousal similarities in ancestral background in the ABCD study compared to other studies may explain the pattern of associations between estimated autozygosity, EA, and cognitive ability in the current study.

Why We Swab: A library of stories in stem cell donation.

Stories are powerful in their ability to disseminate information in a meaningful way. We hypothesized that a stem cell donation story library optimized for social media could support the education and recruitment of committed unrelated hematopoietic stem cell donors from needed demographic groups. We developed Why We Swab, a library of stories on stem cell donation (facebook.com/WhyWeSwab; instagram.com/WhyWeSwab; twitter.com/WhyWeSwab), and evaluated its impact across social and traditional media as well as on eligible potential donors' knowledge and attitudes towards donation. As of December 2021, the library included 28 story arcs featuring 45 storytellers from diverse ancestral backgrounds, including 8 donor-recipient stories. Overall, the stories reached >92,000 people across social media. Notably, stories were republished by 18 print/ broadcast media outlets in Canada and by major medical organizations. A series of stories shown to 33 eligible potential donors improved mean total scores on a donation knowledge test (64% to 85%, p < 0.001), reduced mean ambivalence scale scores (3.85 to 2.70, p < 0.001), and improved participants' willingness to register as donors (45% to 73%, p < 0.005). Data are also shown demonstrating that stakeholders valued the library and that its deployment was associated with improved donor recruitment outcomes in Canada. Why We Swab is accessible and relevant to a wide audience, including stem cell donor registries and recruitment organizations seeking to improve their recruitment efforts as well as to blood and organ & tissue donation organizations who can adapt the Why We Swab model to their audiences.

Marriage in the Melting Pot: An Evolutionary Approach to European Ancestry, Homogamy, and Fertility in the United States.

To understand marriage patterns, homogamy, and fertility of women of European ancestry in the United States from an evolutionary perspective, we investigated if a prevalence of ancestral homogamy exists, the factors influencing a female preference for an ancestral homogamous vs. heterogamous marriage, and if ancestral homogamous vs. heterogamous marriages have an impact on fertility. Furthermore, we aim to determine the heritability of homogamous vs. heterogamous marriage behavior. We used the census data of 369,121 women in the United States married only once and aged between 46 and 60 years, provided by IPUMS USA (https://usa.ipums.org/usa/). We used linear mixed models to determine the association between the probability of a homogamous vs. heterogamous marriage and the individual fertility of women. We aimed to estimate the heritability (genetics and parental environment) of marriage behavior using a linear mixed model. We found that ancestral heterogamous marriages are more frequent compared to homogamous marriages, but only if all ancestry groups are included. If ancestry is aggregated, homogamous marriages are more frequent compared to heterogamous marriages. Most of the variance (up to 27%) in inter-ancestry marriage and fertility (up to 12%) is explained by ancestry per se, followed by the ratio of individuals of a certain ancestral background in a county (∼6%), indicating a frequency depending selection into marriage: the more individuals of a certain ancestry live in a county, the lower is the tendency to marry someone of a different ancestral background. Furthermore, we found that about 12% (depending to some extent on the clustering) of the marriage behavior is heritable. Being in a homogamous marriage and the income of the spouse are both significantly positively associated with the number of children women have and the probability that women have at least one child, albeit explaining only a very low proportion of the overall variance. The most important factor (in terms of variance explained) for being in an ancestral homogamous vs. heterogamous marriage, for the number of children, and for childlessness is the ancestry of the women. Most children are born to women of Irish, French, and Norwegian ancestry (Irish X̄: 3.24, French X̄: 3.21, and Norwegian X̄: 3.18), the lowest number of children is to women of Latvian, Rumanian, and Russian ancestry (Latvian X̄: 2.26, Rumanian X̄: 2.19, and Russian X̄: 2.35). Albeit, we are not able to distinguish the genetic and social heritability on the basis of our data, only a small heritability for in-group vs. out-group marriage behavior is indicated (∼12% of variance explained).

A locus at 19q13.31 significantly reduces the ApoE ε4 risk for Alzheimer's Disease in African Ancestry.

African descent populations have a lower Alzheimer disease risk from ApoE ε4 compared to other populations. Ancestry analysis showed that the difference in risk between African and European populations lies in the ancestral genomic background surrounding the ApoE locus (local ancestry). Identifying the mechanism(s) of this protection could lead to greater insight into the etiology of Alzheimer disease and more personalized therapeutic intervention. Our objective is to follow up the local ancestry finding and identify the genetic variants that drive this risk difference and result in a lower risk for developing Alzheimer disease in African ancestry populations. We performed association analyses using a logistic regression model with the ApoE ε4 allele as an interaction term and adjusted for genome-wide ancestry, age, and sex. Discovery analysis included imputed SNP data of 1,850 Alzheimer disease and 4,331 cognitively intact African American individuals. We performed replication analyses on 63 whole genome sequenced Alzheimer disease and 648 cognitively intact Ibadan individuals. Additionally, we reproduced results using whole-genome sequencing of 273 Alzheimer disease and 275 cognitively intact admixed Puerto Rican individuals. A further comparison was done with SNP imputation from an additional 8,463 Alzheimer disease and 11,365 cognitively intact non-Hispanic White individuals. We identified a significant interaction between the ApoE ε4 allele and the SNP rs10423769_A allele, (β = -0.54,SE = 0.12,p-value = 7.50x10-6) in the discovery data set, and replicated this finding in Ibadan (β = -1.32,SE = 0.52,p-value = 1.15x10-2) and Puerto Rican (β = -1.27,SE = 0.64,p-value = 4.91x10-2) individuals. The non-Hispanic Whites analyses showed an interaction trending in the “protective” direction but failing to pass a 0.05 significance threshold (β = -1.51,SE = 0.84,p-value = 7.26x10-2). The presence of the rs10423769_A allele reduces the odds ratio for Alzheimer disease risk from 7.2 for ApoE ε4/ε4 carriers lacking the A allele to 2.1 for ApoE ε4/ε4 carriers with at least one A allele. This locus is located approximately 2 mB upstream of the ApoE locus, in a large cluster of pregnancy specific beta-1 glycoproteins on chromosome 19 and lies within a long noncoding RNA, ENSG00000282943.This study identified a new African-ancestry specific locus that reduces the risk effect of ApoE ε4 for developing Alzheimer disease. The mechanism of the interaction with ApoEε4 is not known but suggests a novel mechanism for reducing the risk for ε4 carriers opening the possibility for potential ancestry-specific therapeutic intervention.

EE97 Population Discordance in Economic Evaluations of Polygenic Risk Scores

Polygenic risk scores (PRS) aggregate variants at multiple genetic loci to calculate the likelihood of developing a specific disease. These scores are developed using databases of individuals who have undergone testing, most from European ancestry. This may reduce accuracy for patients of underrepresented ancestral backgrounds. Economic models assessing the value of PRS without exploring the accuracy when used in a diverse population may inaccurately estimate the value of testing, leading to inappropriate coverage, reimbursement, and clinical implementation decisions.

Abstract 2173: Ancestry bias in CRISPR guide design impedes discovery of genetic dependencies

Abstract Socioeconomic factors and discrimination play major roles in variable cancer treatment outcomes across individuals from different ancestral backgrounds. Tumors from patients of different ancestry groups also have divergent patterns of somatic and germline alterations. This led us to hypothesize that these molecular differences may also contribute to the variable treatment outcomes observed in the clinic. We hypothesized that the ancestry of cell lines would impact their genetic dependencies. To test this hypothesis, we leveraged The Cancer Dependency Map (DepMap) which has performed genome-wide CRISPR screens across &amp;gt;1,000 cell lines and &amp;gt;30 cancer types. We first leveraged variant calls from WES/WGS to infer cell line ancestry, then correlated these ancestries with DepMap gene dependency scores. This analysis was underpowered to detect differences in cell lines of African, American, and South Asian descent, since cell lines from these ancestry groups are poorly represented in DepMap, and in cancer research models in general. We were, however, able to detect 71 gene dependencies that were associated with either European or East Asian ancestry. Since different ancestry groups have divergent patterns of germline alterations, we reasoned that specific germline alterations may result in ancestry-associated dependencies. Surprisingly, we identified cis-QTLs for &amp;gt;75% of the ancestry-associated genes. We originally hypothesized that these variants would alter the function of the encoded protein, but instead found that these variants mapped to the targeting sequences of the sgRNA. This suggests that ancestry-associated mismatches within sgRNA targeting sequences can preclude Cas9-mediated genome editing. To understand this problem systematically, we mapped the germline variants that were catalogued in gnomAD to multiple genome-wide CRISPR libraries. The fraction of affected genes differed from library to library and was typically between 2-5%, but we found that individuals of African descent were consistently more affected by this problem across all CRISPR libraries. This is important because it suggests that cell lines of African descent have a higher rate of false negatives in all CRISPR-based experiments. In total, we identified a subset of genes that have ancestry-associated dependency profiles. Most of these genes are the result of ancestry-associated mismatches within the sgRNA targeting sequences. However, many of these genes are not, and require further investigation to understand the influence of ancestry on these genetic dependencies. Citation Format: Sean Alexander Misek, Aaron Fultineer, Jeremie Kalfon, Javad Noorbakhsh, Isabella Boyle, Joshua Dempster, Lia Petronio, Katherine Huang, James McFarland, Rameen Beroukhim, Jesse Boehm. Ancestry bias in CRISPR guide design impedes discovery of genetic dependencies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2173.

Abstract 1223: Accurate inference of genetic ancestry from cancer-derived data

Abstract Introduction: For multiple cancer types, epidemiological data exhibit strong correlations between, on the one hand, the incidence of the disease, its severity when diagnosed, and its clinical outcome, and, on the other hand, the ancestral background of the patient. Recent studies point to genetic and phenotypic differences between tumors in patient populations with differing genetic ancestries, and to the need for more data collection to power research in this area. We sought to facilitate such analysis by developing computational tools for genetic ancestry inference from cancer-derived molecular data, without the need for the patient’s cancer-free genotype or self-declared race or ethnicity. The ability to perform such inference accurately would unlock vast amounts of such data for ancestry-oriented studies of cancer from two major sources. One is the body of data stored by similar massive digital repositories. The other is the body of archival tumor tissues from which molecular data may be generated. Methods: We developed methods for genetic ancestry inference from cancer-derived whole exomes, transcriptomes and targeted gene panels, in the absence of matching cancer-free genomic data. These are adaptive, endowed with the ability to optimize their performance for each input cancer-derived molecular profile. As a result, these inference methods perform consistently, and with quantifiable accuracy, across a range of profiling depths and qualities, and mitigate cancer-related damage to the genome, such as somatic copy-number variation. Results: We examined the performance of these tools with molecular data from three cancer types: pancreatic and ovarian cancers as representative of epithelial tumor types, and acute myeloid leukemia as an example of hematopoietic malignancy. Three molecular data types were considered: whole-exome sequences, exome sequences targeting a panel of cancer-related genes and RNA sequences. The inference accuracy was found to be consistently above 97% across the three cancers and the three data types. Conclusion: Our study demonstrates the feasibility of accurate inference of genetic ancestry from cancer-derived data, with no need for matching cancer-free genotypes. Computational tools for this purpose will be made available as open-source software. Citation Format: Pascal Belleau, Astrid Deschênes, David A. Tuveson, Alexander Krasnitz. Accurate inference of genetic ancestry from cancer-derived data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1223.

A Search for Eurasian Sheep Relationships: Genomic Assessment of the Autochthonous Sheep Breeds in Russia and the Persian Plateau

Genomic assessment of local sheep breeds is relevant to the reconstruction of post-domestication migrations and to filling in gaps in the developmental history and contemporary phylogeographic-differentiation patterns in Eurasia. In this study, we aimed to reveal possible genetic relationships between local sheep breeds in Russia and the Persian Highlands (Iran) based on high-density SNP genotypes. All samples (n = 395) from 11 Iranian and 10 Russian sheep breeds were genotyped by using the Ovine Infinium HD BeadChip (Illumina, San Diego, CA, USA). Principal Component Analysis, maximum-likelihood assessment, and Neighbor-Net graph analysis demonstrated a clear differentiation between Russian sheep breeds of European ancestry from the Iranian local cluster and Russian breeds of Asian origin. Admixture analysis revealed a shared ancestral background, which was detected in several Iranian-local and Russian-local fat-tailed coarse-wool sheep breeds. Our findings contribute to a better understanding of the pattern of historic admixture, which is present in the genomes of many Eurasian sheep breeds.

Influence of ancestry in racial disparities of squamous cell lung cancer.

e20554 Background: Significant progress has been made in the screening, diagnosis, and treatment of squamous cell carcinomas of the lung (LUSC). Despite the advancements, African American populations continue to experience worse disease burden and poorer overall survival, even after controlling for patient and tumor characteristics. While the interplay of various social determinants of health is well known to contribute to racial disparities in cancers, the molecular basis of racial disparity is less understood. Given the diversity of the US population that comprise of genetically admixed groups, understanding the role of ancestry and its influence on biology of cancers that drive incidence and prognosis is paramount to reducing racial disparities. Therefore, in this study, we aimed to investigate the influence of African (AFR) ancestry in genetic mutations of LUSC. Methods: We utilized The Cancer Genome Ancestry Atlas (TCGAA) to obtain data on the genetic ancestry and ancestral composition of 504 LUSC patients. The dataset contained 459 self-reported whites, 32 blacks, and 11 Asians. The percentage of each patient’s ancestral composition (European, AFR, Asian, and Native American) was revealed via the LAMP technique. The dominant ancestry was defined as those with genetic composition of ≥50% from one of four ancestral backgrounds. Genetic alteration profiles and clinical data of patients were obtained from LUSC TCGA PanCancer Atlas through GDC data portal. Of those with AFR dominant ancestry, we analyzed the differences in the gene mutation frequency based upon the proportion of AFR ancestry. Results: Ancestry analysis uncovered 30 AFR ancestry dominant cases with a mean AFR composition of 78.4%. We found 14 subjects with &gt; 80% AFR ancestry and 16 subjects with 50-80% AFR ancestry. Two patients from the &gt; 80% were excluded from the mutational analyses due to absence of genetic profiles in the data portal. TP53 was the most frequently mutated gene with a rate of 91.7% and 87.5% in &gt; 80% and 50-80% AFR groups, respectively. Evaluation of the classic genetic mutations that drive disease pathology in LUSC (EGFR, ALK, PIK3CA, NRAS, KRAS) revealed 25% of &gt; 80% AFR ancestry subjects carried mutations in at least one of these genes compared to 6.3% in the 50-80% AFR ancestry subjects. Also, a trend towards worse overall survival (OS) was seen in those with greater proportion of AFR ancestry (median OS of 27.2 months in &gt; 80% group vs 43.9 months in 50-80% group). Conclusions: Despite the limited sample size, our study highlights substantial heterogeneity in tumor biology even within those of AFR ancestry and that genetic ancestry may impact tumor and host biology that contribute to disparities. Moving forward, engagement of the African American community into clinical trials and genomic studies are needed to explore ancestral influence on tumorigenesis, and to facilitate discovery of new actionable targets to help eradicate racial disparities in lung cancer.

136-OR: Polygenic Scores Improve the Predictive Accuracy of Type 1 Diabetes Classification Algorithms in a Large Biobank Cohort

Introduction: Many biobanks use machine learning algorithms to predict patient phenotypes such as type 1 diabetes (T1D) . It is not known how these algorithms perform in patients with different ancestral backgrounds or whether incorporating genetic data improves phenotypic classification. Methods: We examined 40,843 patients in the Mass General Brigham (MGB) Biobank, including 34,870 white patients and 4,872 non-white patients. The MGB machine learning algorithm predicted 242 patients to have T1D. After applying a gold standard diagnosis based on chart review, we assessed accuracy of the MGB algorithm in different self-reported races and genetic ancestries. We divided the dataset into separate training and validation cohorts, and we constructed a logistic regression model using the machine learning algorithm and previously published T1D polygenic scores to classify patients as T1D cases or controls. Results: The MGB machine learning algorithm for T1D had a positive predictive value of 77.8% for white patients, but only 62.2% for non-white patients (p = 0.04) . Among patients with predominantly European genetic ancestry, adding a polygenic score derived from European populations to the MGB classification algorithm improved the area under the receiver operating curve (AUC) from 0.928 to 0.974 (p &amp;lt; 0.05) . Among patients whose predominant genetic ancestry was not European, adding a polygenic score derived from African populations improved the AUC from 0.889 to 0.920 (p &amp;gt; 0.05) . In both cases, the improvement in AUC was less substantial when using non-ancestry-matched polygenic scores. Conclusions: Automated prediction tools for T1D are imperfect, and performance may differ by patient race. Incorporating ancestry-specific polygenic scores into phenotyping algorithms can improve diagnostic accuracy. This may help reduce healthcare and research disparities by refining the automated classification of T1D in all racial and ancestral groups. Disclosure A.J.Deutsch: None. T.Majarian: Employee; Vertex Pharmaceuticals Incorporated. J.M.Mercader: None. J.C.Florez: Consultant; AstraZeneca, Goldfinch Bio, Inc., Other Relationship; AstraZeneca, Merck &amp; Co., Inc., Novo Nordisk. M.Udler: None. Funding National Institutes of Health (K23DK114551, T32DK007028)

Reliable determination of genetic ancestry from cancer-derived molecular data.

e13588 Background: There is ample epidemiological evidence that, for multiple cancer types, incidence, stage at presentation and outcome correlate strongly with the patient’s race or ethnicity. Recent examination of cancer data repositories such as TCGA has revealed has revealed, for a number of cancers, ancestry dependence of somatic mutation spectrum and transcriptional phenotype. Further progress in genetic ancestry-oriented cancer research requires the ability to perform accurate and robust ancestry inference from existing cancer-derived data, including whole exomes, transcriptomes and targeted gene panels, very often in the absence of matching cancer-free genomic data. Such inference is potentially challenging, given widespread somatic alterations in tumor genomes, observed in multiple types of cancer. Methods: In order to optimize and assess the performance of the ancestry inference for any given input cancer-derived molecular profile, we develop a data synthesis framework. In its core procedure, the ancestral background of the profiled patient is replaced with one of any number of individuals with known ancestry. We then infer the substitute individual’s ancestry, using well-established methods of population genetics and relying on the 1000 Genomes collection as a population reference data set. Data synthesis is applicable to multiple profiling platforms and makes it possible to assess the performance of inference specifically for a given molecular profile, and separately for each continental-level ancestry. This ability extends to all ancestries, including those without statistically sufficient representation in the existing cancer data. Results: We test our approach for three representative cancer types: pancreatic and ovarian cancers as representative of epithelial tumor types, and acute myeloid leukemia as an example of hematopoietic malignancy. We consider tumor-derived data acquired by the whole-exome sequencing, by exome sequencing restricted to a panel of cancer-associated genes, and by RNA sequencing. For all three cancer types, and across the three sequencing platforms, we demonstrate that global, continental-level ancestry of the patient can be inferred accurately and robustly. Specifically, we find the inferred ancestries to be in at least 97% agreement with the golden standard of the ancestry derived from the matching cancer-free genomes. We further show that our inference procedure is accurate and robust in a wide range of sequencing depths. Conclusions: Our study demonstrates that vast amounts of existing cancer-derived molecular data are amenable to ancestry-oriented studies of the disease, without recourse to matching cancer-free genomes or patients' self-identification by ancestry. Furthermore, the procedure we developed facilitates ancestry-oriented research using archived tumor tissue specimens, for which matching cancer-free specimens may not be available.

MP05-06 GENETIC ANALYSIS OF KIDNEY STONE DISEASE IN A MULTI-ETHNIC COHORT: INSIGHTS FROM GENOME-WIDE AND PHENOME-WIDE ASSOCIATION STUDIES

You have accessJournal of UrologyCME1 May 2022MP05-06 GENETIC ANALYSIS OF KIDNEY STONE DISEASE IN A MULTI-ETHNIC COHORT: INSIGHTS FROM GENOME-WIDE AND PHENOME-WIDE ASSOCIATION STUDIES Parth Patel, Vidhya Venkateswaran, Bogdan Pasanuic, and Kymora Scotland Parth PatelParth Patel More articles by this author , Vidhya VenkateswaranVidhya Venkateswaran More articles by this author , Bogdan PasanuicBogdan Pasanuic More articles by this author , and Kymora ScotlandKymora Scotland More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002522.06AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Nephrolithiasis, a common global ailment with significant clinical and economic health burden, has demonstrated heritability up to 56%. Various single nucleotide polymorphisms (SNPs) have been implicated in the development of kidney stone disease. Existing literature regarding this association is primarily in the form of genome-wide association studies or based on geographically limited samples. This genome- and phenome-wide association study aimed to evaluate the link between SNPs and kidney stone disease in a database of patients representing diverse ancestral backgrounds. METHODS: We retrospectively studied our repository of more than 27000 genotyped patients and their de-identified electronic health records. ICD-10 codes were aggregated to provide clinically meaningful groupings called phecodes. Genome-wide association testing was performed between all genotyped SNPs and phecodes associated with urolithiasis. We also tested the association between selected SNPs from our genome-wide association analysis and 1330 phecodes in the biobank to ascertain other phenotypic associations. RESULTS: The ancestry breakdown of these patients was 72.8% European, 16.3% Admixed American, 7.41% Eastern Asian, and 3.45% African. The lead SNPs from the trans-ancestry meta-analysis were rs2263090 and rs79616469 with p-values approaching genome-wide significance threshold of 5e-08 (Figure 1). In the phenome-wide association analysis, SNP rs2263090 showed associations with other kidney-related traits such as hematuria in EUR (Figure 2). CONCLUSIONS: While numerous polymorphisms have been associated with kidney stone disease, our genome-wide and phenome-wide association studies suggest that their phenotypic expression may not be equal across genetic ancestral groupings. This promotes the concept that inheritable causes of nephrolithiasis are likely polygenic and their expression multifactorial, and much still remains to be learned about the molecular basis of kidney stone formation. Source of Funding: N/A © 2022 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 207Issue Supplement 5May 2022Page: e69 Advertisement Copyright & Permissions© 2022 by American Urological Association Education and Research, Inc.MetricsAuthor Information Parth Patel More articles by this author Vidhya Venkateswaran More articles by this author Bogdan Pasanuic More articles by this author Kymora Scotland More articles by this author Expand All Advertisement PDF DownloadLoading ...

Racial and Ethnic Disparities in Multiple Sclerosis Prevalence.

Background and ObjectivesThe goal of this work was to determine whether the prevalence of multiple sclerosis (MS) varies by race and ethnicity.MethodsWe conducted a retrospective cohort study of >2.6 million adults from the multiethnic, community-dwelling members of Kaiser Permanente Southern California. The complete electronic health records of individuals with at least 1 ICD-9 code for MS between January 1, 2008 and December 31, 2010 were reviewed. MS prevalence and 95% CIs stratified by age, sex, and race and ethnicity among 2010 members were estimated with binomial regression. Age- and sex-standardized prevalence was estimated according to the 2010 US Census population.ResultsWe identified 3,863 patients with MS. The average age of patients with prevalent MS was 51.7 years (SD 13.1 years), and 76.8% were women. The female preponderance was more pronounced among Black (81.2%) and Asian (83.6%) than White (76.3%) or Hispanic (74.5%) individuals with MS. Age- and sex-standardized MS prevalence per 100,000 was similarly high among Black (225.8, 95% CI 207.1–244.5) and White (237.7, 95% CI 228.2–247.2) and significantly lower among Hispanic (69.9, 95% CI 64.4–75.5) and Asian (22.6, 95% CI 17.1–28.1) persons. MS prevalence was highest between the ages of 35 and 64 years and declined after 65 years of age across all racial and ethnic groups. Among adults 18 to 24 years of age, the crude MS prevalence was low but was highest among Black and Hispanic young adults, lower in White people, and lowest in Asian/Pacific Islander individuals (48.5, 25.0, 18.0, and 7.1 per 100,000, respectively).DiscussionMS prevalence varies by race and ethnicity, being similarly high in White and Black and significantly lower in Hispanic and Asian persons in Southern California. Taken together with previous studies, these findings indicate that the burden of MS in the US Black community has long been underrecognized. More studies are needed to determine whether MS is an emerging disease among US Hispanic adults and whether MS susceptibility and prevalence vary among Hispanic or Asian individuals from different cultures or ancestral backgrounds.

Genetic architecture of RNA editing regulation in Alzheimer's disease across diverse ancestral populations.

Most Alzheimer's disease (AD)-associated genetic variants do not change protein coding sequence and thus likely exert their effects through regulatory mechanisms. RNA editing, the post-transcriptional modification of RNA bases, is a regulatory feature that is altered in AD patients that differs across ancestral backgrounds. Editing QTLs (edQTLs) are DNA variants that influence the level of RNA editing at a specific site. To study the relationship of DNA variants genome-wide, and particularly in AD-associated loci, with RNA editing, we performed edQTL analyses in self-reported individuals of African American (AF) or White (EU) race with corresponding global genetic ancestry averaging 82.2% African ancestry (AF) and 96.8% European global ancestry (EU) in the two groups, respectively. We used whole-genome genotyping array and RNA sequencing data from peripheral blood of 216AD cases and 212 age-matched, cognitively intact controls. We identified 2144 edQTLs in AF and 3579 in EU, of which 1236 were found in both groups. Among these, edQTLs in linkage disequilibrium (r2 > 0.5) with AD-associated genetic variants in the SORL1, SPI1 and HLA-DRB1 loci were associated with sites that were differentially edited between AD cases and controls. While there is some shared RNA editing regulatory architecture, most edQTLs had distinct effects on the rate of RNA editing in different ancestral populations suggesting a complex architecture of RNA editing regulation. Altered RNA editing may be one possible mechanism for the functional effect of AD-associated variants and may contribute to observed differences in the genetic etiology of AD between ancestries.

Genetics of Type 2 Diabetes: Implications from Large-Scale Studies.

Purpose of ReviewType 2 diabetes (T2D) is a multifactorial, heritable syndrome characterized by dysregulated glucose homeostasis that results from impaired insulin secretion and insulin resistance. Genetic association studies have successfully identified hundreds of T2D risk loci implicating many genes in disease pathogenesis. In this review, we provide an overview of the recent T2D genetic studies from the past 3 years with particular focus on the effects of sample size and ancestral diversity on genetic discovery as well as discuss recent work on the use and limitations of genetic risk scores (GRS) for T2D risk prediction.Recent FindingsRecent large-scale, multi-ancestry genetic studies of T2D have identified over 500 novel risk loci. The genetic variants (i.e., single nucleotide polymorphisms (SNPs)) marking these novel loci in general have smaller effect sizes than previously discovered loci. Inclusion of samples from diverse ancestral backgrounds shows a few ancestry specific loci marked by common variants, but overall, the majority of loci discovered are common across ancestries. Inclusion of common variant GRS, even with hundreds of loci, does not substantially increase T2D risk prediction over standard clinical risk factors such as age and family history.SummaryCommon variant association studies of T2D have now identified over 700 T2D risk loci, half of which have been discovered in the past 3 years. These recent studies demonstrate that inclusion of ancestrally diverse samples can enhance locus discovery and improve accuracy of GRS for T2D risk prediction. GRS based on common variants, however, only minimally enhances risk prediction over standard clinical risk factors.

Admixture Mapping of Sepsis in European Individuals With African Ancestries.

Sepsis is a severe systemic inflammatory response to infections that is accompanied by organ dysfunction. Although the ancestral genetic background is a relevant factor for sepsis susceptibility, there is a lack of studies using the genetic singularities of a recently admixed population to identify loci involved in sepsis susceptibility. Here we aimed to discover new sepsis loci by completing the first admixture mapping study of sepsis in Canary Islanders, leveraging their distinctive genetic makeup as a mixture of Europeans and African ancestries. We used a case-control approach and inferred local ancestry blocks from genome-wide data from 113,414 polymorphisms genotyped in 343 patients with sepsis and 410 unrelated controls, all ascertained for grandparental origin in the Canary Islands (Spain). Deviations in local ancestries between cases and controls were tested using logistic regressions, followed by fine-mapping analyses based on imputed genotypes, in silico functional assessments, and gene expression analysis centered on the region of interest. The admixture mapping analysis detected that local European ancestry in a locus spanning 1.2 megabases of chromosome 8p23.1 was associated with sepsis (lowest p = 1.37 × 10−4; Odds Ratio [OR] = 0.51; 95%CI = 0.40–0.66). Fine-mapping studies prioritized the variant rs13249564 within intron 1 of MFHAS1 gene associated with sepsis (p = 9.94 × 10−4; OR = 0.65; 95%CI = 0.50–0.84). Functional and gene expression analyses focused on 8p23.1 allowed us to identify alternative genes with possible biological plausibility such as defensins, which are well-known effector molecules of innate immunity. By completing the first admixture mapping study of sepsis, our results revealed a new genetic locus (8p23.1) harboring a number of genes with plausible implications in sepsis susceptibility.

Duplex real-time PCR methods for molecular detection and characterization of canine tick-borne haemoparasites from Punjab state, India.

BackgroundMicroscopy is a routinely used technique for the diagnosis of canine tick-borne haemoparasitic diseases in various clinical laboratories worldwide. In an attempt to provide better diagnostic assay to the clients for effective management of these diseases duplex real-time PCR assays were applied.Methods and resultsBlood samples (n = 338) aseptically collected from suspected dogs of Central Plain Zone of Punjab state, India were subjected to SYBR Green based real-time duplex PCR assays for simultaneous detection of B. vogeli & E. canis and B. gibsoni & H. canis. Results revealed an overall prevalence rate of canine tick-borne haemoparasites as 54.1%, amongst which H. canis was the predominant (25.4%), followed by B. gibsoni (16.3%), E. canis (10.7%) and B. vogeli (1.8%). Sensitivity and specificity of the duplex assays ranged from 59.04 to 100.0% and 58.12 to 92.52%, respectively and their strength of agreement was ″fair″ with kappa value statistics. A significant (p < 0.05) association between prevalence of B. gibsoni, H. canis and E. canis infection with risk factors like sex, breed, season and location was recorded. The ancestral background of the field isolates of haemoparasites was also studied by phylogenetic analysis of their nucleotide sequences.ConclusionsSYBR Green dye based duplex real-time PCR assays proved to be highly sensitive, specific, rapid and affordable diagnostic tests for use by clinicians to save the life of pets.Supplementary InformationThe online version contains supplementary material available at 10.1007/s11033-022-07286-4.

Distribution of 54 polygenic risk scores for common diseases in long lived individuals and their offspring.

A surprising and well-replicated result in genetic studies of human longevity is that centenarians appear to carry disease-associated variants in numbers similar to the general population. With the proliferation of large genome-wide association studies (GWAS) in recent years, investigators have turned to polygenic scores to leverage GWAS results into a measure of genetic risk that can better predict the risk of disease than individual significant variants alone. We selected 54 polygenic risk scores (PRSs) developed for a variety of outcomes, and we calculated their values in individuals from the New England Centenarian Study (NECS, N = 4886) and the Long Life Family Study (LLFS, N = 4577). We compared the distribution of these PRSs among exceptionally long-lived individuals (ELLI), their offspring, and controls, and we also examined their predictive values, using t-tests and regression models adjusting for sex and principal components reflecting the ancestral background of the individuals (PCs). In our analyses, we controlled for multiple testing using a Bonferroni-adjusted threshold for 54 traits. We found that only 4 of the 54 PRSs differed between ELLIs and controls in both cohorts. ELLIs had significantly lower mean PRSs for Alzheimer's disease (AD) and coronary artery disease (CAD) than controls, suggesting a genetic predisposition to extreme longevity may be mediated by reduced susceptibility to these traits. ELLIs also had significantly higher mean PRSs for improved cognitive function and parental extreme longevity. In addition, the PRS for AD was associated with a higher risk of dementia among controls but not ELLIs (p = 0.003, 0.3 in NECS, p = 0.03, 0.9 in LLFS, respectively). ELLIs have a similar burden of genetic disease risk as the general population for most traits but have a significantly lower genetic risk of AD and CAD. The lack of association between AD PRS and dementia among ELLIs suggests that the genetic risk for AD that they do have is somehow counteracted by protective genetic or environmental factors.

Interferon pathway lupus risk alleles modulate risk of death from acute COVID-19

Type I interferon (IFN) is critical in our defense against viral infections. Increased type I IFN pathway activation is a genetic risk factor for systemic lupus erythematosus (SLE), and a number of common risk alleles contribute to the high IFN trait. We hypothesized that these common gain-of-function IFN pathway alleles may be associated with protection from mortality in acute COVID-19. We studied patients admitted with acute COVID-19 (756 European-American and 398 African-American ancestry). Ancestral backgrounds were analyzed separately, and mortality after acute COVID-19 was the primary outcome. In European-American ancestry, we found that a haplotype of interferon regulatory factor 5 (IRF5) and alleles of protein kinase cGMP-dependent 1 (PRKG1) were associated with mortality from COVID-19. Interestingly, these were much stronger risk factors in younger patients (OR = 29.2 for PRKG1 in ages 45–54). Variants in the IRF7 and IRF8 genes were associated with mortality from COVID-19 in African-American subjects, and these genetic effects were more pronounced in older subjects. Combining genetic information with blood biomarker data such as C-reactive protein, troponin, and D-dimer resulted in significantly improved predictive capacity, and in both ancestral backgrounds the risk genotypes were most relevant in those with positive biomarkers (OR for death between 14 and 111 in high risk genetic/biomarker groups). This study confirms the critical role of the IFN pathway in defense against COVID-19 and viral infections, and supports the idea that some common SLE risk alleles exert protective effects in antiviral immunity.

Adolescent Verbal Memory as a Psychosis Endophenotype: A Genome-Wide Association Study in an Ancestrally Diverse Sample.

Verbal memory impairment is one of the most prominent cognitive deficits in psychosis. However, few studies have investigated the genetic basis of verbal memory in a neurodevelopmental context, and most genome-wide association studies (GWASs) have been conducted in European-ancestry populations. We conducted a GWAS on verbal memory in a maximum of 11,017 participants aged 8.9 to 11.1 years in the Adolescent Brain Cognitive Development Study®, recruited from a diverse population in the United States. Verbal memory was assessed by the Rey Auditory Verbal Learning Test, which included three measures of verbal memory: immediate recall, short-delay recall, and long-delay recall. We adopted a mixed-model approach to perform a joint GWAS of all participants, adjusting for ancestral background and familial relatedness. The inclusion of participants from all ancestries increased the power of the GWAS. Two novel genome-wide significant associations were found for short-delay and long-delay recall verbal memory. In particular, one locus (rs9896243) associated with long-delay recall was mapped to the NSF (N-Ethylmaleimide Sensitive Factor, Vesicle Fusing ATPase) gene, indicating the role of membrane fusion in adolescent verbal memory. Based on the GWAS in the European subset, we estimated the SNP-heritability to be 15% to 29% for the three verbal memory traits. We found that verbal memory was genetically correlated with schizophrenia, providing further evidence supporting verbal memory as an endophenotype for psychosis.