Characterizing Race/Ethnicity and Genetic Ancestry for 100,000 Subjects in the Genetic Epidemiology Research on Adult Health and Aging (GERA) Cohort

Rare variant analyses in 51,256 type 2 diabetes cases and 370,487 controls reveal the pathogenicity spectrum of monogenic diabetes genes

Type 2 diabetes (T2D) genome-wide association studies (GWASs) often overlook rare variants as a result of previous imputation panels' limitations and scarce whole-genome sequencing (WGS) data. We used TOPMed imputation and WGS to conduct the largest T2D GWAS meta-analysis involving 51,256 cases of T2D and 370,487 controls, targeting variants with a minor allele frequency as low as 5 × 10-5. We identified 12 new variants, including a rare African/African American-enriched enhancer variant near the LEP gene (rs147287548), associated with fourfold increased T2D risk. We also identified a rare missense variant in HNF4A (p.Arg114Trp), associated with eightfold increased T2D risk, previously reported in maturity-onset diabetes of the young with reduced penetrance, but observed here in a T2D GWAS. We further leveraged these data to analyze 1,634 ClinVar variants in 22 genes related to monogenic diabetes, identifying two additional rare variants in HNF1A and GCK associated with fivefold and eightfold increased T2D risk, respectively, the effects of which were modified by the individual's polygenic risk score. For 21% of the variants with conflicting interpretations or uncertain significance in ClinVar, we provided support of being benign based on their lack of association with T2D. Our work provides a framework for using rare variant GWASs to identify large-effect variants and assess variant pathogenicity in monogenic diabetes genes.

Advancing Equity in Rare Disease Research: Insights From the Undiagnosed Disease Network

Rare diseases affect 6%-8% of the population and present diagnostic challenges, particularly for historically marginalized ethnic and racial groups. The Undiagnosed Diseases Network (UDN) aims to enhance diagnosis rates and research participation among such minoritized groups. A retrospective review was conducted from 2015 to 2023, analyzing 2235 UDN participants to evaluate its progress toward this objective. Data on demographics, disease phenotypes, diagnostic outcomes, and socioeconomic factors were collected and statistical analyses assessed differences among ethnic and racial groups. This demonstrated that Hispanic and Black non-Hispanic groups were underrepresented, while White non-Hispanic participants were overrepresented in the UDN compared to the US population. Individuals whose primary language was not English were also significantly underrepresented. Diagnosis rates varied, with the highest rates among Asian non-Hispanic (39.5%) and Hispanic (35.3%) groups and the lowest rate in the White non-Hispanic group (26.8%) (p < 0.001). Binomial logistic regression found, however, that only participant age and disease phenotype predicted the likelihood of receiving a diagnosis (p < 0.001). Persistent ethnic and racial disparities in UDN participation appear to be associated with major differences in application rates. Under-enrollment of historically marginalized ethnic and racial groups may be due to economic hardships and language barriers. No differences in the diagnostic yield among ethnic and racial groups were observed after controlling for other factors. This work highlights the value of comprehensive genetic evaluations for addressing healthcare disparities and suggests priorities for advancing inclusion in rare disease research.

Association of lipid-lowering drugs with the risk of type 2 diabetes and its complications: a mendelian randomized study

BACKGROUND

The pathogenesis of type 2 diabetes mellitus is somewhat associated with lipid metabolism. We aim to assess the impact of lipid-lowering drugs (HMGCR inhibitors, PCSK9 inhibitors, and NPC1L1 inhibitors) on type 2 diabetes mellitus and its complications through a two-sample Mendelian randomization (MR) study.

METHOD

We identified suitable genetic instruments from the GWAS database that represent the expression levels of three genes, interpreting reduced genetically proxied gene expression as indicative of lipid-lowering drug use. We evaluated the causal relationships among these variables employing a two-sample Mendelian randomization approach, with the Inverse Variance Weighted (IVW) analysis serving as the primary method. Coronary artery disease was utilized as a positive control to validate the reliability of the selected genetic instruments.

RESULT

Increased genetically proxied HMGCR expression is significantly associated with a reduced risk of type 2 diabetes mellitus (OR = 0.64, 95%CI = 0.55-0.74), which was replicated in the FinnGen study with consistent results (OR = 0.65, 95%CI = 0.53-0.80). Increased genetically proxied HMGCR expression is associated with a reduced risk of diabetic retinopathy (OR = 0.23, 95%CI = 0.12-0.44) and diabetic nephropathy (OR = 0.35, 95%CI = 0.17-0.71). In contrast, increased genetically proxied PCSK9 expression is associated with a decreased risk of diabetic coma (OR = 0.70, 95%CI = 0.50-0.98), diabetic neuropathy (OR = 0.24, 95%CI = 0.14-0.42), diabetic retinopathy (OR = 0.67, 95%CI = 0.48-0.96), diabetic cardiovascular diseases (OR = 0.62, 95%CI = 0.38-0.99), and diabetic nephropathy (OR = 0.62, 95%CI = 0.41-0.95).

CONCLUSIONS

This Mendelian randomization study suggests an association between HMGCR and the pathogenesis of type 2 diabetes mellitus, with increased genetically proxied HMGCR expression reducing the risk of type 2 diabetes mellitus, while PCSK9 and NPC1L1 show no significant association with type 2 diabetes mellitus. These findings may offer more reasonable lipid-lowering drug options for patients with dyslipidemia.

Multiple measures for self-identification improve matching donors with patients in unrelated hematopoietic stem cell transplant

BACKGROUND

Questions persist around whether and how to use race or geographic ancestry in biomedical research and medicine, but these forms of self-identification serve as a critical tool to inform matching algorithms for human leukocyte antigen (HLA) of varying levels of resolution for unrelated hematopoietic stem cell transplant in large donor registries.

METHODS

Here, we examined multiple self-reported measures of race and ancestry from a survey of a cohort of over 100,000 U.S. volunteer bone marrow donors alongside their high-resolution HLA genotype data.

RESULTS

We find that these self-report measures are often non-overlapping, and that no single self-reported measure alone provides a better fit to HLA genetic ancestry than a combination including both race and geographic ancestry. We also found that patterns of reporting for race and ancestry appear to be influenced by participation in direct-to-consumer genetic ancestry testing.

CONCLUSIONS

While these data are not used directly in matching for transplant, our results demonstrate that there is a place for the language of both race and geographic ancestry in the critical process of facilitating accurate prediction of HLA in the donor registry context.

Research Priorities in Pediatric Asthma Morbidity: Addressing the Impacts of Systemic Racism on Children with Asthma in the United States. An Official American Thoracic Society Workshop Report

Background: In the United States, Black and Latino children with asthma are more likely than White children with asthma to require emergency department visits or hospitalizations because of an asthma exacerbation. Although many cite patient-level socioeconomic status and access to health care as primary drivers of disparities, there is an emerging focus on a major root cause of disparities-systemic racism. Current conceptual models of asthma disparities depict the historical and current effects of systemic racism as the foundation for unequal exposures to social determinants of health, environmental exposures, epigenetic factors, and differential healthcare access and quality. These ultimately lead to biologic changes over the life course resulting in asthma morbidity and mortality. Methods: At the 2022 American Thoracic Society International Conference, a diverse panel of experts was assembled to identify gaps and opportunities to address systemic racism in childhood asthma research. Panelists found that to examine and address the impacts of systemic racism on children with asthma, researchers and medical systems that support biomedical research will need to 1) address the current gaps in our understanding of how to conceptualize and characterize the impacts of systemic racism on child health, 2) design research studies that leverage diverse disciplines and engage the communities affected by systemic racism in identifying and designing studies to evaluate interventions that address the racialized system that contributes to disparities in asthma health outcomes, and 3) address funding mechanisms and institutional research practices that will be needed to promote antiracism practices in research and its dissemination. Results: A thorough literature review and expert opinion discussion demonstrated that there are few studies in childhood asthma that identify systemic racism as a root cause of many of the disparities seen in children with asthma. Community engagement and participation in research studies is essential to design interventions to address the racialized system in which patients and families live. Dissemination and implementation studies with an equity lens will provide the multilevel evaluations required to understand the impacts of interventions to address systemic racism and the downstream impacts. To address the impacts of systemic racism and childhood asthma, there needs to be increased training for research teams, funding for studies addressing research that evaluates the impacts of racism, funding for diverse and multidisciplinary research teams including community members, and institutional and financial support of advocating for policy changes based on study findings. Conclusions: Innovative study design, new tools to identify the impacts of systemic racism, community engagement, and improved infrastructure and funding are all needed to support research that will address impacts of systemic racism on childhood asthma outcomes.

Heterogeneity in the effect of type 2 diabetes on dementia incidence in a diverse cohort of Asian American and non-Latino White older adults

Dementia incidence is lower among Asian Americans than among Whites, despite higher prevalence of type 2 diabetes, a well-known dementia risk factor. Determinants of dementia, including type 2 diabetes, have rarely been studied in Asian Americans. We followed 4846 Chinese, 4129 Filipino, 2784 Japanese, 820 South Asian, and 123 360 non-Latino White members of a California-based integrated health-care delivery system from 2002 to 2020. We estimated dementia incidence rates by race/ethnicity and type 2 diabetes status, and we fitted Cox proportional hazards and Aalen additive hazards models for the effect of type 2 diabetes (assessed 5 years before baseline) on age of dementia diagnosis, controlling for sex/gender, educational attainment, nativity, height, race/ethnicity, and a race/ethnicity × diabetes interaction. Type 2 diabetes was associated with higher dementia incidence in Whites (hazard ratio [HR] = 1.46; 95% CI, 1.40-1.52). Compared with Whites, the estimated effect of diabetes was larger in South Asians (HR = 2.26; 95% CI, 1.48-3.44), slightly smaller in Chinese (HR = 1.32; 95% CI, 1.08-1.62) and Filipino (HR = 1.31; 95% CI, 1.08-1.60) individuals, and similar in Japanese individuals (HR = 1.44; 95% CI, 1.15-1.81). Heterogeneity in this association across Asian subgroups may be related to type 2 diabetes severity. Understanding this heterogeneity may inform prevention strategies to prevent dementia for all racial and ethnic groups.

Analysis of ductal carcinoma in situ by self-reported race reveals molecular differences related to outcome

BACKGROUND

Ductal carcinoma in situ (DCIS) is a non-obligate precursor to invasive breast cancer (IBC). Studies have indicated differences in DCIS outcome based on race or ethnicity, but molecular differences have not been investigated.

METHODS

We examined the molecular profile of DCIS by self-reported race (SRR) and outcome groups in Black (n = 99) and White (n = 191) women in a large DCIS case-control cohort study with longitudinal follow up.

RESULTS

Gene expression and pathway analyses suggested that different genes and pathways are involved in diagnosis and ipsilateral breast outcome (DCIS or IBC) after DCIS treatment in White versus Black women. We identified differences in ER and HER2 expression, tumor microenvironment composition, and copy number variations by SRR and outcome groups.

CONCLUSIONS

Our results suggest that different molecular mechanisms drive initiation and subsequent ipsilateral breast events in Black versus White women.

Impact of Genetic Ancestry on T-cell Acute Lymphoblastic Leukemia Outcomes

The influence of genetic ancestry on biology, survival outcomes, and risk stratification in T-cell Acute Lymphoblastic Leukemia (T-ALL) has not been explored. Genetic ancestry was genomically-derived from DNA-based single nucleotide polymorphisms in children and young adults with T-ALL treated on Children's Oncology Group trial AALL0434. We determined associations of genetic ancestry, leukemia genomics and survival outcomes; co-primary outcomes were genomic subtype, pathway alteration, overall survival (OS), and event-free survival (EFS). Among 1309 patients, T-ALL molecular subtypes varied significantly by genetic ancestry, including increased frequency of genomically defined ETP-like, MLLT10, and BCL11B-activated subtypes in patients of African ancestry. In multivariable Cox models adjusting for high-risk subtype and pathways, patients of Admixed American ancestry had superior 5-year EFS/OS compared with European; EFS/OS for patients of African and European ancestry were similar. The prognostic value of five commonly altered T-ALL genes varied by ancestry - including NOTCH1 , which was associated with superior OS for patients of European and Admixed American ancestry but non-prognostic among patients of African ancestry. Furthermore, a published five-gene risk classifier accurately risk stratified patients of European ancestry, but misclassified patients of African ancestry. We developed a penalized Cox model which successfully risk stratified patients across ancestries. Overall, 80% of patients had a genomic alteration in at least one gene with differential prognostic impact by genetic ancestry. T-ALL genomics and prognostic associations of genomic alterations vary by genetic ancestry. These data demonstrate the importance of incorporating genetic ancestry into analyses of tumor biology for risk classification algorithms.

Methods for multiancestry genome-wide association study meta-analysis

Genome-wide association studies (GWAS) have significantly enhanced our understanding of the genetic basis of complex diseases. Despite the technological advancements, gaps in our understanding remain, partly due to small effect sizes and inadequate coverage of genetic variation. Multiancestry GWAS meta-analysis (MAGMA) addresses these challenges by integrating genetic data from diverse populations, thereby increasing power to detect loci and improving fine-mapping resolution to identify causal variants across different ancestry groups. This review provides an overview of the protocols, statistical methods, and software of MAGMA, as well as highlighting some challenges associated with this approach.

Genetic diversity among the present Japanese population: evidence from genotyping of human cell lines established in Japan

Japan is often assumed to have a highly homogeneous ethnic population, because it is an island country. This is evident in human cell lines collected from cell banks; however, these genotypes have not been thoroughly characterized. To examine the population genotypes of human cell lines established in Japan, we conducted SNP genotyping on 57 noncancerous cell lines and 43 lung cancer cell lines. Analysis of biogeographic ancestry revealed that 58 cell lines had non-admixed Japanese genotypes, 21 cell lines had an admixture of Japanese and East Asian genotypes, and the remaining 21 cell lines had East Asian genotypes. The proportion of non-admixed Japanese genotypes was similar between lung cancer and noncancerous cell lines, suggesting that patients in Japan may not exclusively have Japanese genotypes. This could influence the incidence of inherited diseases and should be taken into account in personalized medicine tailored to genetic background. The genetic makeup of the present-day Japanese population cannot be fully explained by the ancestral Jomon and Yayoi lineages. Instead, it is necessary to consider a certain level of genetic admixture between Japanese and neighboring Asian populations. Our study revealed genetic variation among human cell lines derived from Japanese individuals, reflecting the diversity present within the Japanese population.

Polygenic risk and incident coronary heart disease in a large multiethnic cohort

Objective

Many studies support the notion that polygenic risk scores (PRS) improve risk prediction for coronary heart disease (CHD) beyond conventional risk factors. However, PRS are not yet considered risk-enhancing factor in guidelines. Our objective was to determine the predictive performance of a commercially available PRS (CARDIO inCode-Score®) compared with the Pooled Cohorts Equations (PCE) in a contemporary, multi-ethnic cohort.

Methods

Participants (n = 63,070; 67 % female; 18 % non-European) without prior CHD were followed from 2007 through 12/31/2022. The association between the PRS and incident CHD was assessed using Cox regression adjusting for genetic ancestry and risk factors. Event rates were estimated by categories of PCE and by low/intermediate/high genetic risk within PCE categories; risk discrimination and net reclassification improvement (NRI) were also assessed.

Results

There were 3,289 incident CHD events during 14 years of follow-up. Adjusted hazard ratio (aHR) for incident CHD per 1 SD increase in PRS was 1.18 (95 % CI:1.14-1.22), and the aHR for the upper vs lower quintile of the PRS was 1.66 (95 % CI:1.49-1.86). The association was consistent in both sexes, in European participants compared with all minority groups combined and was strongest in the first 5 years of follow-up. The increase in the C-statistic was 0.004 (0.747 vs. 0.751; p < 0.0001); the NRI was 2.4 (0.9-3.8) for the entire cohort and 9.7 (7.5-12.0) for intermediate PCE risk individuals. After incorporating high genetic risk, a further 10 percent of participants at borderline/intermediate PCE risk would be candidates for statin therapy.

Conclusion

Inclusion of polygenic risk improved identification of primary prevention individuals who may benefit from more intensive risk factor modification.

Mammographic density mediates the protective effect of early-life body size on breast cancer risk

The unexplained protective effect of childhood adiposity on breast cancer risk may be mediated via mammographic density (MD). Here, we investigate a complex relationship between adiposity in childhood and adulthood, puberty onset, MD phenotypes (dense area (DA), non-dense area (NDA), percent density (PD)), and their effects on breast cancer. We use Mendelian randomization (MR) and multivariable MR to estimate the total and direct effects of adiposity and age at menarche on MD phenotypes. Childhood adiposity has a decreasing effect on DA, while adulthood adiposity increases NDA. Later menarche increases DA/PD, but when accounting for childhood adiposity, this effect is attenuated. Next, we examine the effect of MD on breast cancer risk. DA/PD have a risk-increasing effect on breast cancer across all subtypes. The MD SNPs estimates are heterogeneous, and additional analyses suggest that different mechanisms may be linking MD and breast cancer. Finally, we evaluate the role of MD in the protective effect of childhood adiposity on breast cancer. Mediation MR analysis shows that 56% (95% CIs [32%-79%]) of this effect is mediated via DA. Our finding suggests that higher childhood adiposity decreases mammographic DA, subsequently reducing breast cancer risk. Understanding this mechanism is important for identifying potential intervention targets.

The role of ethnicity and native-country income in multiple sclerosis: the Italian multicentre study (MS-MigIT)

OBJECTIVE

Multiple sclerosis (MS) is a complex disorder in which environmental and genetic factors interact modifying disease risk and course. This multicentre, case-control study involving 18 Italian MS Centres investigated MS course by ethnicity and native-country economic status in foreign-born patients living in Italy.

METHODS

We identified 457 MS patients who migrated to Italy and 893 age- and sex-matched native-born Italian patients. In our population, 1225 (93.2%) subjects were White Europeans and White Northern Americans (WENA) and 89 (6.8%) patients were from other ethnical groups (OEG); 1109 (82.1%) patients were born in a high-income (HI) Country and 241 (17.9%) in a low-middle-income (LMI) Country. Medical records and patients interviews were used to collect demographic and disease data.

RESULTS

We included 1350 individuals (973 women and 377 men); mean (SD) age was 45.0 (11.7) years. At onset, 25.45% OEG patients vs 12.47% WENA (p = 0.039) had > 3 STIR spine lesions. At recruitment, the same group featured mean (SD) EDSS score of 2.85 (2.23) vs 2.64 (2.28) (p = 0.044) reached in 8.9 (9.0) vs 12.0 (9.0) years (p = 0.018) and underwent 1.10 (4.44) vs. 0.99 (0.40) annual MRI examinations (p = 0.035). At disease onset, patients from LMI countries had higher EDSS score than HI patients (2.40 (1.43) vs 1.99 (1.17); p = 0.032).

DISCUSSION

Our results suggested that both ethnicity and socio-economic status of native country shape MS presentation and course and should be considered for an appropriate management of patients. To the best of our knowledge, this is the first study reporting on the impact of ethnicity in MS at an individual level and beyond an ecological population-perspective.

Multi-tissue transcriptome-wide association study identifies novel candidate susceptibility genes for cataract

Introduction

Cataract is the leading cause of blindness among the elderly worldwide. Twin and family studies support an important role for genetic factors in cataract susceptibility with heritability estimates up to 58%. To date, 55 loci for cataract have been identified by genome-wide association studies (GWAS), however, much work remains to identify the causal genes. Here, we conducted a transcriptome-wide association study (TWAS) of cataract to prioritize causal genes and identify novel ones, and examine the impact of their expression.

Methods

We performed tissue-specific and multi-tissue TWAS analyses to assess associations between imputed gene expression from 54 tissues (including 49 from the Genotype Tissue Expression (GTEx) Project v8) with cataract using FUSION software. Meta-analyzed GWAS summary statistics from 59,944 cataract cases and 478,571 controls, all of European ancestry and from two cohorts (GERA and UK Biobank) were used. We then examined the expression of the novel genes in the lens tissue using the iSyTE database.

Results

Across tissue-specific and multi-tissue analyses, we identified 99 genes for which genetically predicted gene expression was associated with cataract after correcting for multiple testing. Of these 99 genes, 20 (AC007773.1, ANKH, ASIP, ATP13A2, CAPZB, CEP95, COQ6, CREB1, CROCC, DDX5, EFEMP1, EIF2S2, ESRRB, GOSR2, HERC4, INSRR, NIPSNAP2, PICALM, SENP3, and SH3YL1) did not overlap with previously reported cataract-associated loci. Tissue-specific analysis identified 202 significant gene-tissue associations for cataract, of which 166 (82.2%), representing 9 unique genes, were attributed to the previously reported 11q13.3 locus. Tissue-enrichment analysis revealed that gastrointestinal tissues represented one of the highest proportions of the Bonferroni-significant gene-tissue associations (21.3%). Moreover, this gastrointestinal tissue type was the only anatomical category significantly enriched in our results, after correcting for the number of tissue donors and imputable genes for each reference panel. Finally, most of the novel cataract genes (e.g., Capzb) were robustly expressed in iSyTE lens data.

Discussion

Our results provide evidence of the utility of imputation-based TWAS approaches to characterize known GWAS risk loci and identify novel candidate genes that may increase our understanding of cataract etiology. Our findings also highlight the fact that expression of genes associated with cataract susceptibility is not necessarily restricted to lens tissue.

Risk factors affecting polygenic score performance across diverse cohorts

Apart from ancestry, personal or environmental covariates may contribute to differences in polygenic score (PGS) performance. We analyzed effects of covariate stratification and interaction on body mass index (BMI) PGS (PGSBMI) across four cohorts of European (N=491,111) and African (N=21,612) ancestry. Stratifying on binary covariates and quintiles for continuous covariates, 18/62 covariates had significant and replicable R2 differences among strata. Covariates with the largest differences included age, sex, blood lipids, physical activity, and alcohol consumption, with R2 being nearly double between best and worst performing quintiles for certain covariates. 28 covariates had significant PGSBMI-covariate interaction effects, modifying PGSBMI effects by nearly 20% per standard deviation change. We observed overlap between covariates that had significant R2 differences among strata and interaction effects - across all covariates, their main effects on BMI were correlated with their maximum R2 differences and interaction effects (0.56 and 0.58, respectively), suggesting high-PGSBMI individuals have highest R2 and increase in PGS effect. Using quantile regression, we show the effect of PGSBMI increases as BMI itself increases, and that these differences in effects are directly related to differences in R2 when stratifying by different covariates. Given significant and replicable evidence for context-specific PGSBMI performance and effects, we investigated ways to increase model performance taking into account non-linear effects. Machine learning models (neural networks) increased relative model R2 (mean 23%) across datasets. Finally, creating PGSBMI directly from GxAge GWAS effects increased relative R2 by 7.8%. These results demonstrate that certain covariates, especially those most associated with BMI, significantly affect both PGSBMI performance and effects across diverse cohorts and ancestries, and we provide avenues to improve model performance that consider these effects.

Demographic bias in misdiagnosis by computational pathology models

Despite increasing numbers of regulatory approvals, deep learning-based computational pathology systems often overlook the impact of demographic factors on performance, potentially leading to biases. This concern is all the more important as computational pathology has leveraged large public datasets that underrepresent certain demographic groups. Using publicly available data from The Cancer Genome Atlas and the EBRAINS brain tumor atlas, as well as internal patient data, we show that whole-slide image classification models display marked performance disparities across different demographic groups when used to subtype breast and lung carcinomas and to predict IDH1 mutations in gliomas. For example, when using common modeling approaches, we observed performance gaps (in area under the receiver operating characteristic curve) between white and Black patients of 3.0% for breast cancer subtyping, 10.9% for lung cancer subtyping and 16.0% for IDH1 mutation prediction in gliomas. We found that richer feature representations obtained from self-supervised vision foundation models reduce performance variations between groups. These representations provide improvements upon weaker models even when those weaker models are combined with state-of-the-art bias mitigation strategies and modeling choices. Nevertheless, self-supervised vision foundation models do not fully eliminate these discrepancies, highlighting the continuing need for bias mitigation efforts in computational pathology. Finally, we demonstrate that our results extend to other demographic factors beyond patient race. Given these findings, we encourage regulatory and policy agencies to integrate demographic-stratified evaluation into their assessment guidelines.

The Known and Unknown "Knowns" of Human Susceptibility to Coccidioidomycosis

Coccidioidomycosis occurs after inhalation of airborne spores of the endemic, dimorphic fungus, Coccidioides. While the majority of individuals resolve the infection without coming to medical attention, the fungus is a major cause of community-acquired pneumonia in the endemic region, and chronic pulmonary and extrapulmonary disease poses significant personal and economic burdens. This review explores the literature surrounding human susceptibility to coccidioidomycosis, including chronic pulmonary and extrapulmonary dissemination. Over the past century of study, themes have emerged surrounding factors impacting human susceptibility to severe disease or dissemination, including immune suppression, genetic susceptibility, sex, pregnancy, and genetic ancestry. Early studies were observational, frequently with small numbers of cases; several of these early studies are highly cited in review papers, becoming part of the coccidioidomycosis "canon". Specific genetic variants, sex, and immune suppression by TNF inhibitors have been validated in later cohort studies, confirming the original hypotheses. By contrast, some risk factors, such as ABO blood group, Filipino ancestry, or lack of erythema nodosum among black individuals, are repeated in the literature despite the lack of supporting studies or biologic plausibility. Using examination of historical reports coupled with recent cohort and epidemiology studies, evidence for commonly reported risk factors is discussed.

Association between lifetime smoking and cutaneous squamous cell carcinoma: A 2-sample Mendelian randomization study

Background/Purpose

Cutaneous squamous cell carcinoma (cSCC) is one of the most common malignancies worldwide. While several environmental risk factors for cSCC are well established, there is conflicting evidence on cigarette smoking (and its potential causal effect) and cSCC risk. Furthermore, it is unclear if these potential associations represent causal, modifiable risk factors for cSCC development. This study aims to assess the nature of the associations between cigarette smoking traits (smoking initiation, amount smoked, and lifetime smoking exposure) and cSCC risk using two-sample Mendelian randomization analyses.

Methods

Genetic instruments, based on common genetic variants associated with cigarette smoking traits (P < 5 × 10-8), were derived from published genome-wide association studies (GWASs). For cSCC, we used GWAS summary statistics from the Kaiser Permanente GERA cohort (7701 cSCC cases and 60,167 controls; all non-Hispanic Whites).

Results

We found modest evidence that genetically determined lifetime smoking was associated with cSCC (inverse-variance weighted method: OR[95% CI] = 1.47[1.09-1.98]; P = .012), suggesting it may be a causal risk factor for cSCC. We did not detect any evidence of association between genetically determined smoking initiation or amount smoked and cSCC risk.

Conclusion

Study findings highlight the importance of smoking prevention and may support risk-stratified cSCC screening strategies based on carcinogen exposure and other genetic and clinical information.

Evidence supports a causal association between allele-specific vitamin D receptor binding and multiple sclerosis among Europeans

Although evidence exists for a causal association between 25-hydroxyvitamin D (25(OH)D) serum levels, and multiple sclerosis (MS), the role of variation in vitamin D receptor (VDR) binding in MS is unknown. Here, we leveraged previously identified variants associated with allele imbalance in VDR binding (VDR-binding variant; VDR-BV) in ChIP-exo data from calcitriol-stimulated lymphoblastoid cell lines and 25(OH)D serum levels from genome-wide association studies to construct genetic instrumental variables (GIVs). GIVs are composed of one or more genetic variants that serve as proxies for exposures of interest. Here, GIVs for both VDR-BVs and 25(OH)D were used in a two-sample Mendelian Randomization study to investigate the relationship between VDR binding at a locus, 25(OH)D serum levels, and MS risk. Data for 13,598 MS cases and 38,887 controls of European ancestry from Kaiser Permanente Northern California, Swedish MS studies, and the UK Biobank were included. We estimated the association between each VDR-BV GIV and MS. Significant interaction between a VDR-BV GIV and a GIV for serum 25OH(D) was evidence for a causal association between VDR-BVs and MS unbiased by pleiotropy. We observed evidence for associations between two VDR-BVs (rs2881514, rs2531804) and MS after correction for multiple tests. There was evidence of interaction between rs2881514 and a 25(OH)D GIV, providing evidence of a causal association between rs2881514 and MS. This study is the first to demonstrate evidence that variation in VDR binding at a locus contributes to MS risk. Our results are relevant to other autoimmune diseases in which vitamin D plays a role.

Pharmacogenetics and Oxcarbazepine in Children and Adolescents: Beyond HLA-B*15:02

Background: Oxcarbazepine is thought to be better-tolerated and less susceptible to drug-drug interactions than its predecessor, carbamazepine. Genetic testing for HLA-B*15:02 is recommended in specific populations to identify those at high risk of severe hypersensitivity reactions; however, other pharmacologic and pharmacogenetic factors that can impact drug disposition may be involved. Methods: We present a case of an 8-year-old boy treated with oxcarbazepine who developed drug reaction with eosinophilia and systemic symptoms (DRESS) with Stevens-Johnsons syndrome overlap and was negative for HLA-B*15:02. We review the extant literature related to oxcarbazepine disposition, and potential pharmacogenetic variants in aldoketoreductase 1C (AKR1C)2-4 that may contribute to this risk. Results: Genetic variability in oxcarbazepine disposition pathways may contribute to tolerability and toxicity, including the development of hypersensitivity reactions. Conclusions: While preemptive genetic testing for HLA-B*15:02 in individuals of Asian ancestry is recommended to prevent severe hypersensitivity reactions to oxcarbazepine, oxcarbazepine concentrations and AKR1C variation may contribute to the risk of severe adverse reactions. We provide recommendations for future study to elucidate whether these individual factors are important for reducing the risk of severe adverse events.

Major Facilitator Superfamily Domain Containing 5 Inhibition Reduces Lipoprotein(a) Uptake and Calcification in Valvular Heart Disease

BACKGROUND

High circulating levels of Lp(a) (lipoprotein[a]) increase the risk of atherosclerosis and calcific aortic valve disease, affecting millions of patients worldwide. Although atherosclerosis is commonly treated with low-density lipoprotein-targeting therapies, these do not reduce Lp(a) or risk of calcific aortic valve disease, which has no available drug therapies. Targeting Lp(a) production and catabolism may provide therapeutic benefit, but little is known about Lp(a) cellular uptake.

METHODS

Here, unbiased ligand-receptor capture mass spectrometry was used to identify MFSD5 (major facilitator superfamily domain containing 5) as a novel receptor/cofactor involved in Lp(a) uptake.

RESULTS

Reducing MFSD5 expression by a computationally identified small molecule or small interfering RNA suppressed Lp(a) uptake and calcification in primary human valvular endothelial and interstitial cells. MFSD5 variants were associated with aortic stenosis (P=0.027 after multiple hypothesis testing) with evidence suggestive of an interaction with plasma Lp(a) levels.

CONCLUSIONS

MFSD5 knockdown suppressing human valvular cell Lp(a) uptake and calcification, along with meta-analysis of MFSD5 variants associating with aortic stenosis, supports further preclinical assessment of MFSD5 in cardiovascular diseases, the leading cause of death worldwide.

Multi-ancestry genome-wide meta-analysis identifies novel basal cell carcinoma loci and shared genetic effects with squamous cell carcinoma

Basal cell carcinoma (BCC) is one of the most common malignancies worldwide, yet its genetic determinants are incompletely defined. We perform a European ancestry genome-wide association (GWA) meta-analysis and a Hispanic/Latino ancestry GWA meta-analysis and meta-analyze both in a multi-ancestry GWAS meta-analysis of BCC, totaling 50,531 BCC cases and 762,234 controls from four cohorts (GERA, Mass-General Brigham Biobank, UK Biobank, and 23andMe research cohort). Here we identify 122 BCC-associated loci, of which 36 were novel, and subsequently fine-mapped these associations. We also identify an association of the well-known pigment gene SLC45A2 as well as associations at RCC2 and CLPTM1L with BCC in Hispanic/Latinos. We examine these BCC loci for association with cutaneous squamous cell carcinoma (cSCC) in 16,407 SCC cases and 762,486 controls of European ancestry, and 33 SNPs show evidence of association. Our study findings provide important insights into the genetic basis of BCC and cSCC susceptibility.

Genetic ancestry and diagnostic yield of exome sequencing in a diverse population

It has been suggested that diagnostic yield (DY) from Exome Sequencing (ES) may be lower among patients with non-European ancestries than those with European ancestry. We examined the association of DY with estimated continental/subcontinental genetic ancestry in a racially/ethnically diverse pediatric and prenatal clinical cohort. Cases (N = 845) with suspected genetic disorders underwent ES for diagnosis. Continental/subcontinental genetic ancestry proportions were estimated from the ES data. We compared the distribution of genetic ancestries in positive, negative, and inconclusive cases by Kolmogorov-Smirnov tests and linear associations of ancestry with DY by Cochran-Armitage trend tests. We observed no reduction in overall DY associated with any genetic ancestry (African, Native American, East Asian, European, Middle Eastern, South Asian). However, we observed a relative increase in proportion of autosomal recessive homozygous inheritance versus other inheritance patterns associated with Middle Eastern and South Asian ancestry, due to consanguinity. In this empirical study of ES for undiagnosed pediatric and prenatal genetic conditions, genetic ancestry was not associated with the likelihood of a positive diagnosis, supporting the equitable use of ES in diagnosis of previously undiagnosed but potentially Mendelian disorders across all ancestral populations.

Principles and methods for transferring polygenic risk scores across global populations

Polygenic risk scores (PRSs) summarize the genetic predisposition of a complex human trait or disease and may become a valuable tool for advancing precision medicine. However, PRSs that are developed in populations of predominantly European genetic ancestries can increase health disparities due to poor predictive performance in individuals of diverse and complex genetic ancestries. We describe genetic and modifiable risk factors that limit the transferability of PRSs across populations and review the strengths and weaknesses of existing PRS construction methods for diverse ancestries. Developing PRSs that benefit global populations in research and clinical settings provides an opportunity for innovation and is essential for health equity.

Genome-Wide Meta-analysis Identifies Risk Loci and Improves Disease Prediction of Age-Related Macular Degeneration

PURPOSE

To identify age-related macular degeneration (AMD) risk loci and to establish a polygenic prediction model.

DESIGN

Genome-wide association study (GWAS) and polygenic risk score (PRS) construction.

PARTICIPANTS

We included 64 885 European patients with AMD and 568 740 control participants (with overlapped samples) in the UK Biobank, Genetic Epidemiology Research on Aging (GERA), International AMD Consortium, FinnGen, and published early AMD GWASs in meta-analyses, as well as 733 European patients with AMD and 20 487 control participants from the Canadian Longitudinal Study on Aging (CLSA) and non-Europeans from the UK Biobank and GERA for polygenic risk score validation.

METHODS

A multitrait meta-analysis of GWASs comprised 64 885 patients with AMD and 568 740 control participants; the multitrait approach accounted for sample overlap. We constructed a PRS for AMD based on both previously reported as well as unreported AMD loci. We applied the PRS to nonoverlapping data from the CLSA.

MAIN OUTCOME MEASURES

We identified several single nucleotide polymorphisms associated with AMD and established a PRS for AMD risk prediction.

RESULTS

We identified 63 AMD risk loci alongside the well-established AMD loci CFH and ARMS2, including 9 loci that were not reported in previous GWASs, some of which previously were linked to other eye diseases such as glaucoma (e.g., HIC1). We applied our PRS to nonoverlapping data from the CLSA. A new PRS was constructed using the PRS method, PRS-CS, and significantly improved the prediction accuracy of AMD risk compared with PRSs from previously published datasets. We further showed that even people who carry all the well-known AMD risk alleles at CFH and ARMS2 vary considerably in their AMD risk (ranging from close to 0 in individuals with low PRS to > 50% in individuals with high PRS). Although our PRS was derived in individuals of European ancestry, the PRS shows potential for predicting risk in people of East Asian, South Asian, and Latino ancestry.

CONCLUSIONS

Our findings improve the knowledge of the genetic architecture of AMD and help achieve better accuracy in AMD prediction.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Risk factors for inguinal hernia repair among US adults

PURPOSE

To investigate demographic, clinical, and behavioral risk factors for undergoing inguinal hernia repair within a large and ethnically diverse cohort.

METHODS

We conducted a retrospective case-control study from 2007 to 2020 on 302,532 US individuals from a large, integrated healthcare delivery system with electronic health records, who participated in a survey of determinants of health. Participants without diagnosis or procedure record of an inguinal hernia at enrollment were included. We then assessed whether demographic (age, sex, race/ethnicity), clinical, and behavioral factors (obesity status, alcohol use, cigarette smoking and physical activity) were predictors of undergoing inguinal hernia repair using survival analyses. Risk factors showing statistical significance (P < 0.05) in the univariate models were added to a multivariate model.

RESULTS

We identified 7314 patients who underwent inguinal hernia repair over the study period, with a higher incidence in men (6.31%) compared to women (0.53%). In a multivariate model, a higher incidence of inguinal hernia repair was associated with non-Hispanic white race/ethnicity, older age, male sex (aHR = 13.55 [95% confidence interval 12.70-14.50]), and more vigorous physical activity (aHR = 1.24 [0.045]), and alcohol drinker status (aHR = 1.05 [1.00-1.11]); while African-American (aHR = 0.69 [0.59-0.79]), Hispanic/Latino (aHR = 0.84 [0.75-0.91]), and Asian (aHR = 0.35 [0.31-0.39]) race/ethnicity, obesity (aHR = 0.33 [0.31-0.36]) and overweight (aHR = 0.71 [0.67-0.75]) were associated with a lower incidence. The use of cigarette was significantly associated with a higher incidence of inguinal hernia repair in women (aHR 1.23 [1.09-1.40]), but not in men (aHR 0.96 [0.91-1.02]).

CONCLUSION

Inguinal hernia repair is positively associated with non-Hispanic white race/ethnicity, older age, male sex, increased physical activity, alcohol consumption and tobacco use (only in women); while negatively associated with obesity and overweight status. Findings from this large and ethnically diverse study may support future prediction tools to identify patients at high risk of this surgery.

Polygenic risk scores identify heterogeneity in asthma and chronic obstructive pulmonary disease

BACKGROUND

Asthma and chronic obstructive pulmonary disease (COPD) have distinct and overlapping genetic and clinical features.

OBJECTIVE

We sought to test the hypothesis that polygenic risk scores (PRSs) for asthma (PRSAsthma) and spirometry (FEV1 and FEV1/forced vital capacity; PRSspiro) would demonstrate differential associations with asthma, COPD, and asthma-COPD overlap (ACO).

METHODS

We developed and tested 2 asthma PRSs and applied the higher performing PRSAsthma and a previously published PRSspiro to research (Genetic Epidemiology of COPD study and Childhood Asthma Management Program, with spirometry) and electronic health record-based (Mass General Brigham Biobank and Genetic Epidemiology Research on Adult Health and Aging [GERA]) studies. We assessed the association of PRSs with COPD and asthma using modified random-effects and binary-effects meta-analyses, and ACO and asthma exacerbations in specific cohorts. Models were adjusted for confounders and genetic ancestry.

RESULTS

In meta-analyses of 102,477 participants, the PRSAsthma (odds ratio [OR] per SD, 1.16 [95% CI, 1.14-1.19]) and PRSspiro (OR per SD, 1.19 [95% CI, 1.17-1.22]) both predicted asthma, whereas the PRSspiro predicted COPD (OR per SD, 1.25 [95% CI, 1.21-1.30]). However, results differed by cohort. The PRSspiro was not associated with COPD in GERA and Mass General Brigham Biobank. In the Genetic Epidemiology of COPD study, the PRSAsthma (OR per SD: Whites, 1.3; African Americans, 1.2) and PRSspiro (OR per SD: Whites, 2.2; African Americans, 1.6) were both associated with ACO. In GERA, the PRSAsthma was associated with asthma exacerbations (OR, 1.18) in Whites; the PRSspiro was associated with asthma exacerbations in White, LatinX, and East Asian participants.

CONCLUSIONS

PRSs for asthma and spirometry are both associated with ACO and asthma exacerbations. Genetic prediction performance differs in research versus electronic health record-based cohorts.

Genetic risk prediction in Hispanics/Latinos: milestones, challenges, and social-ethical considerations

Genome-wide association studies (GWAS) have allowed the identification of disease-associated variants, which can be leveraged to build polygenic scores (PGSs). Even though PGSs can be a valuable tool in personalized medicine, their predictive power is limited in populations of non-European ancestry, particularly in admixed populations. Recent efforts have focused on increasing racial and ethnic diversity in GWAS, thus, addressing some of the limitations of genetic risk prediction in these populations. Even with these efforts, few studies focus exclusively on Hispanics/Latinos. Additionally, Hispanic/Latino populations are often considered a single population despite varying admixture proportions between and within ethnic groups, diverse genetic heterogeneity, and demographic history. Combined with highly heterogeneous environmental and socioeconomic exposures, this diversity can reduce the transferability of genetic risk prediction models. Given the recent increase of genomic studies that include Hispanics/Latinos, we review the milestones and efforts that focus on genetic risk prediction, summarize the potential for improving PGS transferability, and highlight the challenges yet to be addressed. Additionally, we summarize social-ethical considerations and provide ideas to promote genetic risk prediction models that can be implemented equitably.

Pharmacologic and Genetic Downregulation of Proprotein Convertase Subtilisin/Kexin Type 9 and Survival From Sepsis

OBJECTIVES

Treatments that prevent sepsis complications are needed. Circulating lipid and protein assemblies-lipoproteins play critical roles in clearing pathogens from the bloodstream. We investigated whether early inhibition of proprotein convertase subtilisin/kexin type 9 (PCSK9) may accelerate bloodstream clearance of immunogenic bacterial lipids and improve sepsis outcomes.

DESIGN

Genetic and clinical epidemiology, and experimental models.

SETTING

Human genetics cohorts, secondary analysis of a phase 3 randomized clinical trial enrolling patients with cardiovascular disease (Evaluation of Cardiovascular Outcomes After an Acute Coronary Syndrome During Treatment With Alirocumab [ODYSSEY OUTCOMES]; NCT01663402), and experimental murine models of sepsis.

PATIENTS OR SUBJECTS

Nine human cohorts with sepsis (total n = 12,514) were assessed for an association between sepsis mortality and PCSK9 loss-of-function (LOF) variants. Incident or fatal sepsis rates were evaluated among 18,884 participants in a post hoc analysis of ODYSSEY OUTCOMES. C57BI/6J mice were used in Pseudomonas aeruginosa and Staphylococcus aureus bacteremia sepsis models, and in lipopolysaccharide-induced animal models.

INTERVENTIONS

Observational human cohort studies used genetic PCSK9 LOF variants as instrumental variables. ODYSSEY OUTCOMES participants were randomized to alirocumab or placebo. Mice were administered alirocumab, a PCSK9 inhibitor, at 5 mg/kg or 25 mg/kg subcutaneously, or isotype-matched control, 48 hours prior to the induction of bacterial sepsis. Mice did not receive other treatments for sepsis.

MEASUREMENTS AND MAIN RESULTS

Across human cohort studies, the effect estimate for 28-day mortality after sepsis diagnosis associated with genetic PCSK9 LOF was odds ratio = 0.86 (95% CI, 0.67-1.10; p = 0.24). A significant association was present in antibiotic-treated patients. In ODYSSEY OUTCOMES, sepsis frequency and mortality were infrequent and did not significantly differ by group, although both were numerically lower with alirocumab vs. placebo (relative risk of death from sepsis for alirocumab vs. placebo, 0.62; 95% CI, 0.32-1.20; p = 0.15). Mice treated with alirocumab had lower endotoxin levels and improved survival.

CONCLUSIONS

PCSK9 inhibition may improve clinical outcomes in sepsis in preventive, pretreatment settings.

Evaluating genomic polygenic risk scores for childhood acute lymphoblastic leukemia in Latinos

The utility of polygenic risk score (PRS) models has not been comprehensively evaluated for childhood acute lymphoblastic leukemia (ALL), the most common type of cancer in children. Previous PRS models for ALL were based on significant loci observed in genome-wide association studies (GWASs), even though genomic PRS models have been shown to improve prediction performance for a number of complex diseases. In the United States, Latino (LAT) children have the highest risk of ALL, but the transferability of PRS models to LAT children has not been studied. In this study, we constructed and evaluated genomic PRS models based on either non-Latino White (NLW) GWAS or a multi-ancestry GWAS. We found that the best PRS models performed similarly between held-out NLW and LAT samples (PseudoR2 = 0.086 ± 0.023 in NLW vs. 0.060 ± 0.020 in LAT), and can be improved for LAT if we performed GWAS in LAT-only (PseudoR2 = 0.116 ± 0.026) or multi-ancestry samples (PseudoR2 = 0.131 ± 0.025). However, the best genomic models currently do not have better prediction accuracy than a conventional model using all known ALL-associated loci in the literature (PseudoR2 = 0.166 ± 0.025), which includes loci from GWAS populations that we could not access to train genomic PRS models. Our results suggest that larger and more inclusive GWASs may be needed for genomic PRS to be useful for ALL. Moreover, the comparable performance between populations may suggest a more oligogenic architecture for ALL, where some large effect loci may be shared between populations. Future PRS models that move away from the infinite causal loci assumption may further improve PRS for ALL.

Rare variant association analysis in 51,256 type 2 diabetes cases and 370,487 controls informs the spectrum of pathogenicity of monogenic diabetes genes

We meta-analyzed array data imputed with the TOPMed reference panel and whole-genome sequence (WGS) datasets and performed the largest, rare variant (minor allele frequency as low as 5×10-5) GWAS meta-analysis of type 2 diabetes (T2D) comprising 51,256 cases and 370,487 controls. We identified 52 novel variants at genome-wide significance (p<5 × 10-8), including 8 novel variants that were either rare or ancestry-specific. Among them, we identified a rare missense variant in HNF4A p.Arg114Trp (OR=8.2, 95% confidence interval [CI]=4.6-14.0, p = 1.08×10-13), previously reported as a variant implicated in Maturity Onset Diabetes of the Young (MODY) with incomplete penetrance. We demonstrated that the diabetes risk in carriers of this variant was modulated by a T2D common variant polygenic risk score (cvPRS) (carriers in the top PRS tertile [OR=18.3, 95%CI=7.2-46.9, p=1.2×10-9] vs carriers in the bottom PRS tertile [OR=2.6, 95% CI=0.97-7.09, p = 0.06]. Association results identified eight variants of intermediate penetrance (OR>5) in monogenic diabetes (MD), which in aggregate as a rare variant PRS were associated with T2D in an independent WGS dataset (OR=4.7, 95% CI=1.86-11.77], p = 0.001). Our data also provided support evidence for 21% of the variants reported in ClinVar in these MD genes as benign based on lack of association with T2D. Our work provides a framework for using rare variant imputation and WGS analyses in large-scale population-based association studies to identify large-effect rare variants and provide evidence for informing variant pathogenicity.

The mediating role of mammographic density in the protective effect of early-life adiposity on breast cancer risk: a multivariable Mendelian randomization study

Observational studies suggest that mammographic density (MD) may have a role in the unexplained protective effect of childhood adiposity on breast cancer risk. Here, we investigated a complex and interlinked relationship between puberty onset, adiposity, MD, and their effects on breast cancer using Mendelian randomization (MR). We estimated the effects of childhood and adulthood adiposity, and age at menarche on MD phenotypes (dense area (DA), non-dense area (NDA), percent density (PD)) using MR and multivariable MR (MVMR), allowing us to disentangle their total and direct effects. Next, we examined the effect of MD on breast cancer risk, including risk of molecular subtypes, and accounting for genetic pleiotropy. Finally, we used MVMR to evaluate whether the protective effect of childhood adiposity on breast cancer was mediated by MD. Childhood adiposity had a strong inverse effect on mammographic DA, while adulthood adiposity increased NDA. Later menarche had an effect of increasing DA and PD, but when accounting for childhood adiposity, this effect attenuated to the null. DA and PD had a risk-increasing effect on breast cancer across all subtypes. The MD single-nucleotide polymorphism (SNP) estimates were extremely heterogeneous, and examination of the SNPs suggested different mechanisms may be linking MD and breast cancer. Finally, MR mediation analysis estimated that 56% (95% CIs [32% - 79%]) of the childhood adiposity effect on breast cancer risk was mediated via DA. In this work, we sought to disentangle the relationship between factors affecting MD and breast cancer. We showed that higher childhood adiposity decreases mammographic DA, which subsequently leads to reduced breast cancer risk. Understanding this mechanism is of great importance for identifying potential targets of intervention, since advocating weight gain in childhood would not be recommended.

Prostate cancer genetic alterations in Hispanic men

BACKGROUND

Differences in DNA alterations in prostate cancer among White, Black, and Asian men have been widely described. This is the first description of the frequency of DNA alterations in primary and metastatic prostate cancer samples of self-reported Hispanic men.

METHODS

We utilized targeted next-generation sequencing tumor genomic profiles from prostate cancer tissues that underwent clinical sequencing at academic centers (GENIE 11th). We decided to restrict our analysis to the samples from Memorial Sloan Kettering Cancer Center as it was by far the main contributor of Hispanic samples. The numbers of men by self-reported ethnicity and racial categories were analyzed via Fisher's exact test between Hispanic-White versus non-Hispanic White.

RESULTS AND LIMITATIONS

Our cohort consisted of 1412 primary and 818 metastatic adenocarcinomas. In primary adenocarcinomas, TMPRSS2 and ERG gene alterations were less common in non-Hispanic White men than Hispanic White (31.86% vs. 51.28%, p = 0.0007, odds ratio [OR] = 0.44 [0.27-0.72] and 25.34% vs. 42.31%, p = 0.002, OR = 0.46 [0.28-0.76]). In metastatic tumors, KRAS and CCNE1 alterations were less prevalent in non-Hispanic White men (1.03% vs. 7.50%, p = 0.014, OR = 0.13 [0.03, 0.78] and 1.29% vs. 10.00%, p = 0.003, OR = 0.12 [0.03, 0.54]). No significant differences were found in actionable alterations and androgen receptor mutations between the groups. Due to the lack of clinical characteristics and genetic ancestry in this dataset, correlation with these could not be explored.

CONCLUSION

DNA alteration frequencies in primary and metastatic prostate cancer tumors differ among Hispanic-White and non-Hispanic White men. Notably, we found no significant differences in the prevalence of actionable genetic alterations between the groups, suggesting that a significant number of Hispanic men could benefit from the development of targeted therapies.

Transcriptome-wide association study identifies novel candidate susceptibility genes for migraine

Genome-wide association studies (GWASs) have identified more than 130 genetic susceptibility loci for migraine; however, how most of these loci impact migraine development is unknown. To identify novel genes associated with migraine and interpret the transcriptional products of those genes, we conducted a transcriptome-wide association study (TWAS). We performed tissue-specific and multi-tissue TWAS analyses to assess associations between imputed gene expression from 53 tissues and migraine susceptibility using FUSION software. Meta-analyzed GWAS summary statistics from 26,052 migraine cases and 487,214 controls, all of European ancestry and from two cohorts (the Kaiser Permanente GERA and the UK Biobank), were used. We evaluated the associations for genes after conditioning on variant-level effects from GWAS, and we tested for colocalization of GWAS migraine-associated loci and expression quantitative trait loci (eQTLs). Across tissue-specific and multi-tissue analyses, we identified 53 genes for which genetically predicted gene expression was associated with migraine after correcting for multiple testing. Of these 53 genes, 10 (ATF5, CNTNAP1, KTN1-AS1, NEIL1, NEK4, NNT, PNKP, RUFY2, TUBG2, and VAT1) did not overlap known migraine-associated loci identified from GWAS. Tissue-specific analysis identified 45 gene-tissue pairs and cardiovascular tissues represented the highest proportion of the Bonferroni-significant gene-tissue pairs (n = 22 [49%]), followed by brain tissues (n = 6 [13%]), and gastrointestinal tissues (n = 4 [9%]). Colocalization analyses provided evidence of shared genetic variants underlying eQTL and GWAS signals in 18 of the gene-tissue pairs (40%). Our TWAS reports novel genes for migraine and highlights the important contribution of brain, cardiovascular, and gastrointestinal tissues in migraine susceptibility.

Association of Behavioral and Clinical Risk Factors With Cataract: A Two-Sample Mendelian Randomization Study

Purpose

To investigate the association of genetically determined primary open-angle glaucoma (POAG), myopic refractive error (RE), type 2 diabetes (T2D), blood pressure (BP), body mass index (BMI), cigarette smoking, and alcohol consumption with the risk of age-related cataract.

Methods

To assess potential causal effects of clinical or behavioral factors on cataract risk, we conducted two-sample Mendelian randomization analyses. Genetic instruments, based on common genetic variants associated with risk factors at genome-wide significance (P < 5 × 10-8), were derived from published genome-wide association studies (GWAS). For age-related cataract, we used GWAS summary statistics from our previous GWAS conducted in the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort (28,092 cataract cases and 50,487 controls; all non-Hispanic whites) or in the UK Biobank (31,852 cataract cases and 428,084 controls; all European-descent individuals). We used the inverse-variance weighted (IVW) method as our primary source of Mendelian randomization estimates and conducted common sensitivity analyses.

Results

We found that genetically determined POAG and mean spherical equivalent RE were significantly associated with cataract risk (IVW model: odds ratio [OR] = 1.04; 95% confidence interval [CI], 1.01-1.08; P = 0.018; per diopter more hyperopic: OR = 0.92; 95% CI, 0.89-0.93; P = 6.51 × 10-13, respectively). In contrast, genetically determined T2D, BP, BMI, cigarette smoking, or alcohol consumption were not associated with cataract risk (P > 0.05).

Conclusions

Our results provide evidence that genetic risks for POAG and myopia may be causal risk factors for age-related cataract. These results are consistent with previous observational studies reporting associations of myopia with cataract risk. This information may support population cataract risk stratification and screening strategies.

The power of TOPMed imputation for the discovery of Latino-enriched rare variants associated with type 2 diabetes

AIMS/HYPOTHESIS

The Latino population has been systematically underrepresented in large-scale genetic analyses, and previous studies have relied on the imputation of ungenotyped variants based on the 1000 Genomes (1000G) imputation panel, which results in suboptimal capture of low-frequency or Latino-enriched variants. The National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) released the largest multi-ancestry genotype reference panel representing a unique opportunity to analyse rare genetic variations in the Latino population. We hypothesise that a more comprehensive analysis of low/rare variation using the TOPMed panel would improve our knowledge of the genetics of type 2 diabetes in the Latino population.

METHODS

We evaluated the TOPMed imputation performance using genotyping array and whole-exome sequence data in six Latino cohorts. To evaluate the ability of TOPMed imputation to increase the number of identified loci, we performed a Latino type 2 diabetes genome-wide association study (GWAS) meta-analysis in 8150 individuals with type 2 diabetes and 10,735 control individuals and replicated the results in six additional cohorts including whole-genome sequence data from the All of Us cohort.

RESULTS

Compared with imputation with 1000G, the TOPMed panel improved the identification of rare and low-frequency variants. We identified 26 genome-wide significant signals including a novel variant (minor allele frequency 1.7%; OR 1.37, p=3.4 × 10-9). A Latino-tailored polygenic score constructed from our data and GWAS data from East Asian and European populations improved the prediction accuracy in a Latino target dataset, explaining up to 7.6% of the type 2 diabetes risk variance.

CONCLUSIONS/INTERPRETATION

Our results demonstrate the utility of TOPMed imputation for identifying low-frequency variants in understudied populations, leading to the discovery of novel disease associations and the improvement of polygenic scores.

DATA AVAILABILITY

Full summary statistics are available through the Common Metabolic Diseases Knowledge Portal ( https://t2d.hugeamp.org/downloads.html ) and through the GWAS catalog ( https://www.ebi.ac.uk/gwas/ , accession ID: GCST90255648). Polygenic score (PS) weights for each ancestry are available via the PGS catalog ( https://www.pgscatalog.org , publication ID: PGP000445, scores IDs: PGS003443, PGS003444 and PGS003445).

Leveraging trans-ethnic genetic risk scores to improve association power for complex traits in underrepresented populations

Trans-ethnic genome-wide association studies have revealed that many loci identified in European populations can be reproducible in non-European populations, indicating widespread trans-ethnic genetic similarity. However, how to leverage such shared information more efficiently in association analysis is less investigated for traits in underrepresented populations. We here propose a statistical framework, trans-ethnic genetic risk score informed gene-based association mixed model (GAMM), by hierarchically modeling single-nucleotide polymorphism effects in the target population as a function of effects of the same trait in well-studied populations. GAMM powerfully integrates genetic similarity across distinct ancestral groups to enhance power in understudied populations, as confirmed by extensive simulations. We illustrate the usefulness of GAMM via the application to 13 blood cell traits (i.e. basophil count, eosinophil count, hematocrit, hemoglobin concentration, lymphocyte count, mean corpuscular hemoglobin, mean corpuscular hemoglobin concentration, mean corpuscular volume, monocyte count, neutrophil count, platelet count, red blood cell count and total white blood cell count) in Africans of the UK Biobank (n = 3204) while utilizing genetic overlap shared in Europeans (n = 746 667) and East Asians (n = 162 255). We discovered multiple new associated genes, which had otherwise been missed by existing methods, and revealed that the trans-ethnic information indirectly contributed much to the phenotypic variance. Overall, GAMM represents a flexible and powerful statistical framework of association analysis for complex traits in underrepresented populations by integrating trans-ethnic genetic similarity across well-studied populations, and helps attenuate health inequities in current genetics research for people of minority populations.

A multiethnic genome-wide analysis of 19,420 individuals identifies novel loci associated with axial length and shared genetic influences with refractive error and myopia

Introduction: Long axial length (AL) is a risk factor for myopia. Although family studies indicate that AL has an important genetic component with heritability estimates up to 0.94, there have been few reports of AL-associated loci. Methods: Here, we conducted a multiethnic genome-wide association study (GWAS) of AL in 19,420 adults of European, Latino, Asian, and African ancestry from the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort, with replication in a subset of the Consortium for Refractive Error and Myopia (CREAM) cohorts of European or Asian ancestry. We further examined the effect of the identified loci on the mean spherical equivalent (MSE) within the GERA cohort. We also performed genome-wide genetic correlation analyses to quantify the genetic overlap between AL and MSE or myopia risk in the GERA European ancestry sample. Results: Our multiethnic GWA analysis of AL identified a total of 16 genomic loci, of which 5 are novel. We found that all AL-associated loci were significantly associated with MSE after Bonferroni correction. We also found that AL was genetically correlated with MSE (rg = -0.83; SE, 0.04; p = 1.95 × 10-89) and myopia (rg = 0.80; SE, 0.05; p = 2.84 × 10-55). Finally, we estimated the array heritability for AL in the GERA European ancestry sample using LD score regression, and found an overall heritability estimate of 0.37 (s.e. = 0.04). Discussion: In this large and multiethnic study, we identified novel loci, associated with AL at a genome-wide significance level, increasing substantially our understanding of the etiology of AL variation. Our results also demonstrate an association between AL-associated loci and MSE and a shared genetic basis between AL and myopia risk.

Genetically adjusted PSA levels for prostate cancer screening

Prostate-specific antigen (PSA) screening for prostate cancer remains controversial because it increases overdiagnosis and overtreatment of clinically insignificant tumors. Accounting for genetic determinants of constitutive, non-cancer-related PSA variation has potential to improve screening utility. In this study, we discovered 128 genome-wide significant associations (P < 5 × 10-8) in a multi-ancestry meta-analysis of 95,768 men and developed a PSA polygenic score (PGSPSA) that explains 9.61% of constitutive PSA variation. We found that, in men of European ancestry, using PGS-adjusted PSA would avoid up to 31% of negative prostate biopsies but also result in 12% fewer biopsies in patients with prostate cancer, mostly with Gleason score <7 tumors. Genetically adjusted PSA was more predictive of aggressive prostate cancer (odds ratio (OR) = 3.44, P = 6.2 × 10-14, area under the curve (AUC) = 0.755) than unadjusted PSA (OR = 3.31, P = 1.1 × 10-12, AUC = 0.738) in 106 cases and 23,667 controls. Compared to a prostate cancer PGS alone (AUC = 0.712), including genetically adjusted PSA improved detection of aggressive disease (AUC = 0.786, P = 7.2 × 10-4). Our findings highlight the potential utility of incorporating PGS for personalized biomarkers in prostate cancer screening.

Diagnostic Yield of Exome Sequencing in a Diverse Pediatric and Prenatal Population is not Associated with Genetic Ancestry

Purpose

It has been hypothesized that diagnostic yield (DY) from Exome Sequencing (ES) may be lower among patients with non-European ancestries than those with European ancestry. We examined the association of DY with estimated continental genetic ancestry in a racially/ethnically diverse pediatric and prenatal clinical cohort.

Methods

Cases (N=845) with suspected genetic disorders underwent ES for diagnosis. Continental genetic ancestry proportions were estimated from the ES data. We compared the distribution of genetic ancestries in positive, negative, and inconclusive cases by Kolmogorov Smirnov tests and linear associations of ancestry with DY by Cochran-Armitage trend tests.

Results

We observed no reduction in overall DY associated with any continental genetic ancestry (Africa, America, East Asia, Europe, Middle East, South Asia). However, we observed a relative increase in proportion of autosomal recessive homozygous inheritance versus other inheritance patterns associated with Middle Eastern and South Asian ancestry, due to consanguinity.

Conclusions

In this empirical study of ES for undiagnosed pediatric and prenatal genetic conditions, genetic ancestry was not associated with the likelihood of a positive diagnosis, supporting the ethical and equitable use of ES in diagnosis of previously undiagnosed but potentially Mendelian disorders across all ancestral populations.

TCGA Expression Analyses of 10 Carcinoma Types Reveal Clinically Significant Racial Differences

Epidemiological studies reveal disparities in cancer incidence and outcome rates between racial groups in the United States. In our study, we investigated molecular differences between racial groups in 10 carcinoma types. We used publicly available data from The Cancer Genome Atlas to identify patterns of differential gene expression in tumor samples obtained from 4112 White, Black/African American, and Asian patients. We identified race-dependent expression of numerous genes whose mRNA transcript levels were significantly correlated with patients' survival. Only a small subset of these genes was differentially expressed in multiple carcinomas, including genes involved in cell cycle progression such as CCNB1, CCNE1, CCNE2, and FOXM1. In contrast, most other genes, such as transcriptional factor ETS1 and apoptotic gene BAK1, were differentially expressed and clinically significant only in specific cancer types. Our analyses also revealed race-dependent, cancer-specific regulation of biological pathways. Importantly, homology-directed repair and ERBB4-mediated nuclear signaling were both upregulated in Black samples compared to White samples in four carcinoma types. This large-scale pan-cancer study refines our understanding of the cancer health disparity and can help inform the use of novel biomarkers in clinical settings and the future development of precision therapies.

A new polygenic score for refractive error improves detection of children at risk of high myopia but not the prediction of those at risk of myopic macular degeneration

BACKGROUND

High myopia (HM), defined as a spherical equivalent refractive error (SER) ≤ -6.00 diopters (D), is a leading cause of sight impairment, through myopic macular degeneration (MMD). We aimed to derive an improved polygenic score (PGS) for predicting children at risk of HM and to test if a PGS is predictive of MMD after accounting for SER.

METHODS

The PGS was derived from genome-wide association studies in participants of UK Biobank, CREAM Consortium, and Genetic Epidemiology Research on Adult Health and Aging. MMD severity was quantified by a deep learning algorithm. Prediction of HM was quantified as the area under the receiver operating curve (AUROC). Prediction of severe MMD was assessed by logistic regression.

FINDINGS

In independent samples of European, African, South Asian and East Asian ancestry, the PGS explained 19% (95% confidence interval 17-21%), 2% (1-3%), 8% (7-10%) and 6% (3-9%) of the variation in SER, respectively. The AUROC for HM in these samples was 0.78 (0.75-0.81), 0.58 (0.53-0.64), 0.71 (0.69-0.74) and 0.67 (0.62-0.72), respectively. The PGS was not associated with the risk of MMD after accounting for SER: OR = 1.07 (0.92-1.24).

INTERPRETATION

Performance of the PGS approached the level required for clinical utility in Europeans but not in other ancestries. A PGS for refractive error was not predictive of MMD risk once SER was accounted for.

FUNDING

Supported by the Welsh Government and Fight for Sight (24WG201).

Polygenic Scores Help Reduce Racial Disparities in Predictive Accuracy of Automated Type 1 Diabetes Classification Algorithms

OBJECTIVE

Automated algorithms to identify individuals with type 1 diabetes using electronic health records are increasingly used in biomedical research. It is not known whether the accuracy of these algorithms differs by self-reported race. We investigated whether polygenic scores improve identification of individuals with type 1 diabetes.

RESEARCH DESIGN AND METHODS

We investigated two large hospital-based biobanks (Mass General Brigham [MGB] and BioMe) and identified individuals with type 1 diabetes using an established automated algorithm. We performed medical record reviews to validate the diagnosis of type 1 diabetes. We implemented two published polygenic scores for type 1 diabetes (developed in individuals of European or African ancestry). We assessed the classification algorithm before and after incorporating polygenic scores.

RESULTS

The automated algorithm was more likely to incorrectly assign a diagnosis of type 1 diabetes in self-reported non-White individuals than in self-reported White individuals (odds ratio 3.45; 95% CI 1.54-7.69; P = 0.0026). After incorporating polygenic scores into the MGB Biobank, the positive predictive value of the type 1 diabetes algorithm increased from 70 to 97% for self-reported White individuals (meaning that 97% of those predicted to have type 1 diabetes indeed had type 1 diabetes) and from 53 to 100% for self-reported non-White individuals. Similar results were found in BioMe.

CONCLUSIONS

Automated phenotyping algorithms may exacerbate health disparities because of an increased risk of misclassification of individuals from underrepresented populations. Polygenic scores may be used to improve the performance of phenotyping algorithms and potentially reduce this disparity.

Validation of a Genetic-Enhanced Risk Prediction Model for Colorectal Cancer in a Large Community-Based Cohort

BACKGROUND

Polygenic risk scores (PRS) which summarize individuals' genetic risk profile may enhance targeted colorectal cancer screening. A critical step towards clinical implementation is rigorous external validations in large community-based cohorts. This study externally validated a PRS-enhanced colorectal cancer risk model comprising 140 known colorectal cancer loci to provide a comprehensive assessment on prediction performance.

METHODS

The model was developed using 20,338 individuals and externally validated in a community-based cohort (n = 85,221). We validated predicted 5-year absolute colorectal cancer risk, including calibration using expected-to-observed case ratios (E/O) and calibration plots, and discriminatory accuracy using time-dependent AUC. The PRS-related improvement in AUC, sensitivity and specificity were assessed in individuals of age 45 to 74 years (screening-eligible age group) and 40 to 49 years with no endoscopy history (younger-age group).

RESULTS

In European-ancestral individuals, the predicted 5-year risk calibrated well [E/O = 1.01; 95% confidence interval (CI), 0.91-1.13] and had high discriminatory accuracy (AUC = 0.73; 95% CI, 0.71-0.76). Adding the PRS to a model with age, sex, family and endoscopy history improved the 5-year AUC by 0.06 (P < 0.001) and 0.14 (P = 0.05) in the screening-eligible age and younger-age groups, respectively. Using a risk-threshold of 5-year SEER colorectal cancer incidence rate at age 50 years, adding the PRS had a similar sensitivity but improved the specificity by 11% (P < 0.001) in the screening-eligible age group. In the younger-age group it improved the sensitivity by 27% (P = 0.04) with similar specificity.

CONCLUSIONS

The proposed PRS-enhanced model provides a well-calibrated 5-year colorectal cancer risk prediction and improves discriminatory accuracy in the external cohort.

IMPACT

The proposed model has potential utility in risk-stratified colorectal cancer prevention.

Association of Education With Dementia Incidence Stratified by Ethnicity and Nativity in a Cohort of Older Asian American Individuals

IMPORTANCE

High education protects against dementia, but returns on educational attainment may be different across sociodemographic groups owing to various social factors. Asian American individuals are a growing and diverse group, but little research has assessed dementia determinants in this population.

OBJECTIVE

To examine the association of education with dementia in a large cohort of Asian American individuals, stratifying by ethnicity and nativity.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study used electronic health record (EHR) and survey data from the Research Program on Genes, Environment, and Health and the California Men's Health Study surveys (2002-2020). Data are from Kaiser Permanente Northern California, an integrated health care delivery system. This study used a volunteer sample who completed the surveys. Participants included Chinese, Filipino, and Japanese individuals who were aged 60 to less than 90 years without a dementia diagnosis in the EHR at the time of the survey (baseline) and who had 2 years of health plan coverage before baseline. Data analysis was performed from December 2021 to December 2022.

EXPOSURES

The main exposure was educational attainment (college degree or higher vs less than a college degree), and the main stratification variables were Asian ethnicity and nativity (born in the US or born outside the US).

MAIN OUTCOMES AND MEASURES

The primary outcome was incident dementia diagnosis in the EHR. Dementia incidence rates were estimated by ethnicity and nativity, and Cox proportional hazards and Aalen additive hazards models were fitted for the association of college degree or higher vs less than a college degree with time to dementia, adjusting for age (timescale), sex, nativity, and an interaction between nativity and college degree.

RESULTS

Among 14 749 individuals, the mean (SD) age at baseline was 70.6 (7.3) years, 8174 (55.4%) were female, and 6931 (47.0%) had attained a college degree. Overall, among individuals born in the US, those with a college degree had 12% lower dementia incidence (HR, 0.88; 95% CI, 0.75-1.03) compared with those without at least a college degree, although the confidence interval included the null. The HR for individuals born outside the US was 0.82 (95% CI, 0.72-0.92; P = .46 for the college degree by nativity interaction). The findings were similar across ethnicity and nativity groups except for Japanese individuals born outside the US.

CONCLUSIONS AND RELEVANCE

These findings suggest that college degree attainment was associated with lower dementia incidence, with similar associations across nativity. More work is needed to understand determinants of dementia in Asian American individuals and to elucidate mechanisms linking educational attainment and dementia.

Investigating the association between schizophrenia and distance visual acuity: Mendelian randomisation study

BACKGROUND

Increased rates of visual impairment are observed in people with schizophrenia.

AIMS

We assessed whether genetically predicted poor distance acuity is causally associated with schizophrenia, and whether genetically predicted schizophrenia is causally associated with poorer visual acuity.

METHOD

We used bidirectional, two-sample Mendelian randomisation to assess the effect of poor distance acuity on schizophrenia risk, poorer visual acuity on schizophrenia risk and schizophrenia on visual acuity, in European and East Asian ancestry samples ranging from approximately 14 000 to 500 000 participants. Genetic instrumental variables were obtained from the largest available summary statistics: for schizophrenia, from the Psychiatric Genomics Consortium; for visual acuity, from the UK Biobank; and for poor distance acuity, from a meta-analysis of case-control samples. We used the inverse variance-weighted method and sensitivity analyses to test validity of results.

RESULTS

We found little evidence that poor distance acuity was causally associated with schizophrenia (odds ratio 1.00, 95% CI 0.91-1.10). Genetically predicted schizophrenia was associated with poorer visual acuity (mean difference in logMAR score: 0.024, 95% CI 0.014-0.033) in European ancestry samples, with a similar but less precise effect that in smaller East Asian ancestry samples (mean difference: 0.186, 95% CI -0.008 to 0.379).

CONCLUSIONS

Genetic evidence supports schizophrenia being a causal risk factor for poorer visual acuity, but not the converse. This highlights the importance of visual care for people with psychosis and refutes previous hypotheses that visual impairment is a potential target for prevention of schizophrenia.

Estimation and implications of the genetic architecture of fasting and non-fasting blood glucose

The genetic regulation of post-prandial glucose levels is poorly understood. Here, we characterise the genetic architecture of blood glucose variably measured within 0 and 24 h of fasting in 368,000 European ancestry participants of the UK Biobank. We found a near-linear increase in the heritability of non-fasting glucose levels over time, which plateaus to its fasting state value after 5 h post meal (h² = 11%; standard error: 1%). The genetic correlation between different fasting times is > 0.77, suggesting that the genetic control of glucose is largely constant across fasting durations. Accounting for heritability differences between fasting times leads to a ~16% improvement in the discovery of genetic variants associated with glucose. Newly detected variants improve the prediction of fasting glucose and type 2 diabetes in independent samples. Finally, we meta-analysed summary statistics from genome-wide association studies of random and fasting glucose (N = 518,615) and identified 156 independent SNPs explaining 3% of fasting glucose variance. Altogether, our study demonstrates the utility of random glucose measures to improve the discovery of genetic variants associated with glucose homeostasis, even in fasting conditions.

Accuracy of haplotype estimation and whole genome imputation affects complex trait analyses in complex biobanks

Sample recruitment for research consortia, biobanks, and personal genomics companies span years, necessitating genotyping in batches, using different technologies. As marker content on genotyping arrays varies, integrating such datasets is non-trivial and its impact on haplotype estimation (phasing) and whole genome imputation, necessary steps for complex trait analysis, remains under-evaluated. Using the iPSYCH dataset, comprising 130,438 individuals, genotyped in two stages, on different arrays, we evaluated phasing and imputation performance across multiple phasing methods and data integration protocols. While phasing accuracy varied by choice of method and data integration protocol, imputation accuracy varied mostly between data integration protocols. We demonstrate an attenuation in imputation accuracy within samples of non-European origin, highlighting challenges to studying complex traits in diverse populations. Finally, imputation errors can bias association tests, reduce predictive utility of polygenic scores. Carefully optimized data integration strategies enhance accuracy and replicability of complex trait analyses in complex biobanks.