Limb development genes underlie variation in human fingerprint patterns.

Fingerprints are of long-standing practical and cultural interest, but little is known about the mechanisms that underlie their variation. Using genome-wide scans in Han Chinese cohorts, we identified 18 loci associated with fingerprint type across the digits, including a genetic basis for the long-recognized "pattern-block" correlations among the middle three digits. In particular, we identified a variant near EVI1 that alters regulatory activity and established a role for EVI1 in dermatoglyph patterning in mice. Dynamic EVI1 expression during human development supports its role in shaping the limbs and digits, rather than influencing skin patterning directly. Trans-ethnic meta-analysis identified 43 fingerprint-associated loci, with nearby genes being strongly enriched for general limb development pathways. We also found that fingerprint patterns were genetically correlated with hand proportions. Taken together, these findings support the key role of limb development genes in influencing the outcome of fingerprint patterning.

Genome-wide Association Studies in Ancestrally Diverse Populations: Opportunities, Methods, Pitfalls, and Recommendations.

Genome-wide association studies (GWASs) have focused primarily on populations of European descent, but it is essential that diverse populations become better represented. Increasing diversity among study participants will advance our understanding of genetic architecture in all populations and ensure that genetic research is broadly applicable. To facilitate and promote research in multi-ancestry and admixed cohorts, we outline key methodological considerations and highlight opportunities, challenges, solutions, and areas in need of development. Despite the perception that analyzing genetic data from diverse populations is difficult, it is scientifically and ethically imperative, and there is an expanding analytical toolbox to do it well.

shaPRS: Leveraging shared genetic effects across traits or ancestries improves accuracy of polygenic scores.

We present shaPRS, a method that leverages widespread pleiotropy between traits or shared genetic effects across ancestries, to improve the accuracy of polygenic scores. The method uses genome-wide summary statistics from two diseases or ancestries to improve the genetic effect estimate and standard error at SNPs where there is homogeneity of effect between the two datasets. When there is significant evidence of heterogeneity, the genetic effect from the disease or population closest to the target population is maintained. We show via simulation and a series of real-world examples that shaPRS substantially enhances the accuracy of polygenic risk scores (PRSs) for complex diseases and greatly improves PRS performance across ancestries. shaPRS is a PRS pre-processing method that is agnostic to the actual PRS generation method, and as a result, it can be integrated into existing PRS generation pipelines and continue to be applied as more performant PRS methods are developed over time.

Substitution of a single non-coding nucleotide upstream of TMEM216 causes non-syndromic retinitis pigmentosa and is associated with reduced TMEM216 expression.

Genome analysis of individuals affected by retinitis pigmentosa (RP) identified two rare nucleotide substitutions at the same genomic location on chromosome 11 (g.61392563 [GRCh38]), 69 base pairs upstream of the start codon of the ciliopathy gene TMEM216 (c.-69G>A, c.-69G>T [GenBank: NM_001173991.3]), in individuals of South Asian and African ancestry, respectively. Genotypes included 71 homozygotes and 3 mixed heterozygotes in trans with a predicted loss-of-function allele. Haplotype analysis showed single-nucleotide variants (SNVs) common across families, suggesting ancestral alleles within the two distinct ethnic populations. Clinical phenotype analysis of 62 available individuals from 49 families indicated a similar clinical presentation with night blindness in the first decade and progressive peripheral field loss thereafter. No evident systemic ciliopathy features were noted. Functional characterization of these variants by luciferase reporter gene assay showed reduced promotor activity. Nanopore sequencing confirmed the lower transcription of the TMEM216 c.-69G>T allele in blood-derived RNA from a heterozygous carrier, and reduced expression was further recapitulated by qPCR, using both leukocytes-derived RNA of c.-69G>T homozygotes and total RNA from genome-edited hTERT-RPE1 cells carrying homozygous TMEM216 c.-69G>A. In conclusion, these variants explain a significant proportion of unsolved cases, specifically in individuals of African ancestry, suggesting that reduced TMEM216 expression might lead to abnormal ciliogenesis and photoreceptor degeneration.

The politics of allyship: Multiethnic coalitions and mass attitudes toward protest.

Recent work finds that nonviolent resistance by ethnic minorities is perceived as more violent and requiring more policing than identical resistance by ethnic majorities, reducing its impact and effectiveness. We ask whether allies-advantaged group participants in disadvantaged group movements-can mitigate these barriers. On the one hand, allies can counter negative stereotypes and defuse threat perceptions among advantaged group members, while raising expectations of success and lowering expected risks among disadvantaged group members. On the other hand, allies can entail significant costs, carrying risks of cooptation, replication of power hierarchies, and marginalization of core constituencies. To shed light on this question we draw on the case of the Black Lives Matter (BLM) movement, which, in 2020, attracted unprecedented White participation. Employing a national survey experiment, we find that sizeable White presence at racial justice protests increases protest approval, reduces perceptions of violence, and raises the likelihood of participation among White audiences, while not causing significant backlash among Black audiences. Black respondents mostly see White presence as useful for advancing the movement's goals, and predominant White presence reduces expectations that protests will be forcefully repressed. We complement these results with analysis of tens of thousands of images shared on social media during the 2020 BLM protests, finding a significant association between the presence of Whites in the images and user engagement and amplification. The findings suggest that allyship can be a powerful tool for promoting sociopolitical change amid deep structural inequality.

All human social groups are human, but some are more human than others: A comprehensive investigation of the implicit association of "Human" to US racial/ethnic groups.

All human groups are equally human, but are they automatically represented as such? Harnessing data from 61,377 participants across 13 experiments (six primary and seven supplemental), a sharp dissociation between implicit and explicit measures emerged. Despite explicitly affirming the equal humanity of all racial/ethnic groups, White participants consistently associated Human (relative to Animal) more with White than Black, Hispanic, and Asian groups on Implicit Association Tests (IATs; experiments 1-4). This effect emerged across diverse representations of Animal that varied in valence (pets, farm animals, wild animals, and vermin; experiments 1-2). Non-White participants showed no such Human=Own Group bias (e.g., Black participants on a White-Black/Human-Animal IAT). However, when the test included two outgroups (e.g., Asian participants on a White-Black/Human-Animal IAT), non-White participants displayed Human=White associations. The overall effect was largely invariant across demographic variations in age, religion, and education but did vary by political ideology and gender, with self-identified conservatives and men displaying stronger Human=White associations (experiment 3). Using a variance decomposition method, experiment 4 showed that the Human=White effect cannot be attributed to valence alone; the semantic meaning of Human and Animal accounted for a unique proportion of variance. Similarly, the effect persisted even when Human was contrasted with positive attributes (e.g., God, Gods, and Dessert; experiment 5a). Experiments 5a-b clarified the primacy of Human=White rather than Animal=Black associations. Together, these experiments document a factually erroneous but robust Human=Own Group implicit stereotype among US White participants (and globally), with suggestive evidence of its presence in other socially dominant groups.

Polygenic transcriptome risk scores for COPD and lung function improve cross-ethnic portability of prediction in the NHLBI TOPMed program.

While polygenic risk scores (PRSs) enable early identification of genetic risk for chronic obstructive pulmonary disease (COPD), predictive performance is limited when the discovery and target populations are not well matched. Hypothesizing that the biological mechanisms of disease are shared across ancestry groups, we introduce a PrediXcan-derived polygenic transcriptome risk score (PTRS) to improve cross-ethnic portability of risk prediction. We constructed the PTRS using summary statistics from application of PrediXcan on large-scale GWASs of lung function (forced expiratory volume in 1 s [FEV1] and its ratio to forced vital capacity [FEV1/FVC]) in the UK Biobank. We examined prediction performance and cross-ethnic portability of PTRS through smoking-stratified analyses both on 29,381 multi-ethnic participants from TOPMed population/family-based cohorts and on 11,771 multi-ethnic participants from TOPMed COPD-enriched studies. Analyses were carried out for two dichotomous COPD traits (moderate-to-severe and severe COPD) and two quantitative lung function traits (FEV1 and FEV1/FVC). While the proposed PTRS showed weaker associations with disease than PRS for European ancestry, the PTRS showed stronger association with COPD than PRS for African Americans (e.g., odds ratio [OR] = 1.24 [95% confidence interval [CI]: 1.08-1.43] for PTRS versus 1.10 [0.96-1.26] for PRS among heavy smokers with ≥ 40 pack-years of smoking) for moderate-to-severe COPD. Cross-ethnic portability of the PTRS was significantly higher than the PRS (paired t test p < 2.2 × 10-16 with portability gains ranging from 5% to 28%) for both dichotomous COPD traits and across all smoking strata. Our study demonstrates the value of PTRS for improved cross-ethnic portability compared to PRS in predicting COPD risk.

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.

Trends in inequalities in the prevalence of dementia in the United States.

This paper presents estimates of the prevalence of dementia in the United States from 2000 to 2016 by age, sex, race and ethnicity, education, and a measure of lifetime earnings, using data on 21,442 individuals aged 65 y and older and 97,629 person-year observations from a nationally representative survey, the Health and Retirement Study (HRS). The survey includes a range of cognitive tests, and a subsample underwent clinical assessment for dementia. We developed a longitudinal, latent-variable model of cognitive status, which we estimated using the Markov Chain Monte Carlo method. This model provides more accurate estimates of dementia prevalence in population subgroups than do previously used methods on the HRS. The age-adjusted prevalence of dementia decreased from 12.2% in 2000 (95% CI, 11.7 to 12.7%) to 8.5% in 2016 (7.9 to 9.1%) in the 65+ population, a statistically significant decline of 3.7 percentage points or 30.1%. Females are more likely to live with dementia, but the sex difference has narrowed. In the male subsample, we found a reduction in inequalities across education, earnings, and racial and ethnic groups; among females, those inequalities also declined, but less strongly. We observed a substantial increase in the level of education between 2000 and 2016 in the sample. This compositional change can explain, in a statistical sense, about 40% of the reduction in dementia prevalence among men and 20% among women, whereas compositional changes in the older population by age, race and ethnicity, and cardiovascular risk factors mattered less.

Recommendations for statin management in primary prevention: disparities among international risk scores.

BACKGROUND AND AIMS: Statin recommendations in primary prevention depend upon risk algorithms. Moreover, with intermediate risk, risk enhancers and de-enhancers are advocated to aid decisions. The aim of this study was to compare algorithms used in North America and Europe for the identification of patients warranting statin or consideration of risk enhancers and de-enhancers. METHODS: A simulated population (n = 7680) equal in males and females, with/without smoking, aged 45-70 years, total cholesterol 3.5-7.0 mmol/L, high-density lipoprotein cholesterol 0.6-2.2 mmol/L, and systolic blood pressure 100-170 mmHg, was evaluated. High, intermediate, and low risks were determined using the Framingham Risk Score (FRS), Pooled Cohort Equation (PCE), four versions of Systematic Coronary Risk Evaluation 2 (SCORE2), and Multi-Ethnic Study of Atherosclerosis (MESA) algorithm (0-1000 Agatston Units). RESULTS: Concordance for the three levels of risk varied from 19% to 85%. Both sexes might be considered to have low, intermediate, or high risk depending on the algorithm applied, even with the same burden of risk factors. Only SCORE2 (High Risk and Very High Risk versions) identified equal proportions of males and females with high risk. Excluding MESA, the proportion with moderate risk was 25% (SCORE2, Very High Risk Region), 32% (FRS), 39% (PCE), and 45% (SCORE2, Low Risk Region). CONCLUSION: Risk algorithms differ substantially in their estimation of risk, recommendations for statin treatment, and use of ancillary testing, even in identical patients. These results highlight the limitations of currently used risk-based approaches for addressing lipid-specific risk in primary prevention.

An empirical Bayes approach to improving population-specific genetic association estimation by leveraging cross-population data.

Populations of non-European ancestry are substantially underrepresented in genome-wide association studies (GWAS). As genetic effects can differ between ancestries due to possibly different causal variants or linkage disequilibrium patterns, a meta-analysis that includes GWAS of all populations yields biased estimation in each of the populations and the bias disproportionately impacts non-European ancestry populations. This is because meta-analysis combines study-specific estimates with inverse variance as the weights, which causes biases towards studies with the largest sample size, typical of the European ancestry population. In this paper, we propose two empirical Bayes (EB) estimators to borrow the strength of information across populations although accounting for between-population heterogeneity. Extensive simulation studies show that the proposed EB estimators are largely unbiased and improve efficiency compared to the population-specific estimator. In contrast, even though the meta-analysis estimator has a much smaller variance, it yields significant bias when the genetic effect is heterogeneous across populations. We apply the proposed EB estimators to a large-scale trans-ancestry GWAS of stroke and demonstrate that the EB estimators reduce the variance of the population-specific estimator substantially, with the effect estimates close to the population-specific estimates.

The Apo gene's genetic variants: hidden role in Asian vascular risk.

Vascular risk factors, including diabetes, hypertension, hyperlipidemia, and obesity, pose significant health threats with implications extending to neuropsychiatric disorders such as stroke and Alzheimer's disease. The Asian population, in particular, appears to be disproportionately affected due to unique genetic predispositions, as well as epigenetic factors such as dietary patterns and lifestyle habits. Existing management strategies often fall short of addressing these specific needs, leading to greater challenges in prevention and treatment. This review highlights a significant gap in our understanding of the impact of genetic screening in the early detection and tailored treatment of vascular risk factors among the Asian population. Apolipoprotein, a key player in cholesterol metabolism, is primarily associated with dyslipidemia, yet emerging evidence suggests its involvement in conditions such as diabetes, hypertension, and obesity. While genetic variants of vascular risk are ethnic-dependent, current evidence indicates that epigenetics also exhibits ethnic specificity. Understanding the interplay between Apolipoprotein and genetics, particularly within diverse ethnic backgrounds, has the potential to refine risk stratification and enhance precision in management. For Caucasian carrying the APOA5 rs662799 C variant, pharmacological interventions are recommended, as dietary interventions may not be sufficient. In contrast, for Asian populations with the same genetic variant, dietary modifications are initially advised. Should dyslipidemia persist, the consideration of pharmaceutical agents such as statins is recommended.

Second primary cancer risks according to race and ethnicity among U.S. breast cancer survivors.

Breast cancer survivors have an increased risk of developing second primary cancers, yet risks by race and ethnicity have not been comprehensively described. We evaluated second primary cancer risks among 717,335 women diagnosed with first primary breast cancer (aged 20-84 years and survived ≥1-year) in the SEER registries using standardized incidence ratios (SIRs; observed/expected). SIRs were estimated by race and ethnicity compared with the racial- and ethnic-matched general population, and further stratified by clinical characteristics of the index breast cancer. Poisson regression was used to test for heterogeneity by race and ethnicity. SIRs for second primary cancer differed by race and ethnicity with the highest risks observed among non-Hispanic/Latina Asian American, Native Hawaiian, or other Pacific Islander (AANHPI), non-Hispanic/Latina Black (Black), and Hispanic/Latina (Latina) survivors and attenuated risk among non-Hispanic/Latina White (White) survivors (SIRAANHPI = 1.49, 95% CI = 1.44-1.54; SIRBlack = 1.41, 95% CI = 1.37-1.45; SIRLatina = 1.45, 95% CI = 1.41-1.49; SIRWhite = 1.09, 95% CI = 1.08-1.10; p-heterogeneity<.001). SIRs were particularly elevated among AANHPI, Black, and Latina survivors diagnosed with an index breast cancer before age 50 (SIRs range = 1.88-2.19) or with estrogen receptor-negative tumors (SIRs range = 1.60-1.94). Heterogeneity by race and ethnicity was observed for 16/27 site-specific second cancers (all p-heterogeneity's < .05) with markedly elevated risks among AANHPI, Black, and Latina survivors for acute myeloid and acute non-lymphocytic leukemia (SIRs range = 2.68-3.15) and cancers of the contralateral breast (SIRs range = 2.60-3.01) and salivary gland (SIRs range = 2.03-3.96). We observed striking racial and ethnic differences in second cancer risk among breast cancer survivors. Additional research is needed to inform targeted approaches for early detection strategies and treatment to reduce these racial and ethnic disparities.

Understanding racial/ethnic disparities in COVID-19 mortality using a novel metric: COVID excess mortality percentage.

Prior research on racial/ethnic disparities in COVID-19 mortality has often not considered to what extent they reflect COVID-19-specific factors, versus preexisting health differences. This study examines how racial/ethnic disparities in COVID-19 mortality vary with age, sex, and time period over April-December 2020 in the United States, using mortality from other natural causes as a proxy for underlying health. We study a novel measure, the COVID excess mortality percentage (CEMP), defined as the COVID-19 mortality rate divided by the non-COVID natural mortality rate, converted to a percentage, where the CEMP denominator controls (albeit imperfectly) for differences in population health. Disparities measured using CEMP deviate substantially from those in prior research. In particular, we find very high disparities (up to 12:1) in CEMP rates for Hispanics versus Whites, particularly for nonelderly men. Asians also have elevated CEMP rates versus Whites, which were obscured in prior work by lower overall Asian mortality. Native Americans and Blacks have significant disparities compared with White populations, but CEMP ratios to Whites are lower than ratios reported in other work. This is because the higher COVID-19 mortality for Blacks and Native Americans comes partly from higher general mortality risk and partly from COVID-specific risk.

Trends in Endometrial Cancer Incidence in the United States by Race/Ethnicity and Age of Onset from 2000 to 2019.

Endometrial cancer is one of few cancers that has continued to rise in incidence over the past decade with disproportionate increases in adults younger than 50 years old. We used data from the Surveillance, Epidemiology, and End Results Registry (2000-2019) to examine endometrial cancer incidence trends by race/ethnicity and age of onset among women in the United States. Case counts and proportions, age-adjusted incidence rates (per 100,000), and average annual percent changes were calculated by race/ethnicity, overall and stratified by age of onset (early vs late). We found a disproportionate increase in endometrial cancer incidence among women of color, for both early and late onset endometrial cancer. The highest increases in early onset endometrial cancer (<50 years old) were observed among American Indian/Alaska Native women (4.8), followed by Black (3.3), Hispanic/Latina (3.1), and Asian and Pacific Islander women (2.4), whereas white women (0.9) had the lowest increase. Late onset (>50 years old) endometrial cancer incidence followed a similar pattern, with the greatest increases for women of color. The increasing burden of endometrial cancer among women of color, particularly those younger than 50 years old, is a major public health problem necessitating further research and clinical efforts focused on health equity.

School racial/ethnic composition, effect modification by caring teacher/staff presence, and mid-/late-life depressive symptoms: findings from the Study of Healthy Aging in African Americans.

For Black students in the United States, attending schools with a higher proportion of White students is associated with worse mental and physical health outcomes in adolescence/early adulthood. To our knowledge, no prior studies have evaluated the association between school racial/ethnic composition from kindergarten through grade 12 and later-life mental health. In a cohort of Black adults aged ≥50 years in Northern California who retrospectively reported (2017-2020) school racial/ethnic composition for grades 1, 6, 9, and 12, we assessed the association between attending a school with mostly Black students versus not and mid-/late-life depressive symptoms (8-item Patient-Reported Outcomes Measurement Information System (PROMIS) depression score, standardized to the 2000 US adult population) using age-, sex/gender-, southern US birth-, and parental education-adjusted generalized estimating equations, and assessed effect modification by the presence of a caring teacher/staff member. Levels of later-life depressive symptoms were lower among those who attended schools with mostly Black students in grades 1 and 6 (ß = -0.12 [95% CI, -0.23 to 0.00] and ß = -0.11 [95% CI, -0.22 to 0.00], respectively). In grade 6, this difference was larger for students without an adult at school who cared about them (ß = -0.29 [95% CI, -0.51 to -0.07] vs ß = -0.04 [95% CI, -0.17 to 0.09]). Among Black Americans, experiencing early schooling with mostly Black students may have later-life mental health benefits; this protective association appears more important for students without the presence of caring teachers/staff. This article is part of a Special Collection on Mental Health.

Spinocerebellar ataxia type 10 and Huntington disease-like 2 in Venezuela: Further evidence of two different ancestral founder effects.

INTRODUCTION: The American continent populations have a wide genetic diversity, as a product of the admixture of three ethnic groups: Amerindian, European, and African Sub-Saharan. Spinocerebellar ataxia type 10 (SCA10) and Huntington disease-like 2 (HDL2) have very ancient ancestral origins but are restricted to two populations: Amerindian and African Sub-Saharan, respectively. This study aimed to investigate the genetic epidemiological features of these diseases in Venezuela. METHODS: In-phase haplotypes with the expanded alleles were established in seven unrelated index cases diagnosed with SCA10 and in 11 unrelated index cases diagnosed with HDL2. The origins of remote ancestors were recorded. RESULTS: The geographic origin of the ancestors showed grouping in clusters. SCA10 had a minimal general prevalence of 1:256,174 families in the country, but within the identified geographic clusters, the prevalence ranged from 5 per 100,000 to 43 per 100,000 families. HDL2 had a general prevalence of 1:163,016 families, however, within the clusters, the prevalence ranged from 31 per 100,000 to 60 per 100,000 families. The locus-specific haplotype shared by all families worldwide, including the Venezuelans, supports a single old ancestral origin in each case. CONCLUSION: Knowing the genetic ancestry and geographic origins of patients in Ibero-American mixed populations could have significant diagnostic implications; thus, both diseases in Venezuela should always be first explored in patients with a suggestive phenotype and ancestors coming from the same known geographic clusters.

Setting up a state-of-the-art laboratory in resource limited settings: A case study of the biomedical science research and training centre in Northeast Nigeria.

African science has substantial potential, yet it grapples with significant challenges. Here we describe the establishment of the Biomedical Science Research and Training Centre (BioRTC) in Yobe State, Northeast Nigeria, as a case study of a hub fostering on-continent research and describe strategies to overcome current barriers. We detail the steps taken to establish BioRTC, emphasising the critical importance of stakeholder engagement, community involvement, resource optimisation and collaborations. With its state-of-the-art facilities and commitment to training African scientists, BioRTC is poised to significantly advance neuroscience research and training in the region. Although we are in the early stages of our journey, our model, emphasizing open access and inclusivity, offers a replicable blueprint for neuroscience research development in similar resource-limited settings, promising to enrich the global neuroscience community. We invite the support and collaboration of those who share our vision and believe in our potential.

Whole-genome sequencing of African Americans implicates differential genetic architecture in inflammatory bowel disease.

Whether or not populations diverge with respect to the genetic contribution to risk of specific complex diseases is relevant to understanding the evolution of susceptibility and origins of health disparities. Here, we describe a large-scale whole-genome sequencing study of inflammatory bowel disease encompassing 1,774 affected individuals and 1,644 healthy control Americans with African ancestry (African Americans). Although no new loci for inflammatory bowel disease are discovered at genome-wide significance levels, we identify numerous instances of differential effect sizes in combination with divergent allele frequencies. For example, the major effect at PTGER4 fine maps to a single credible interval of 22 SNPs corresponding to one of four independent associations at the locus in European ancestry individuals but with an elevated odds ratio for Crohn disease in African Americans. A rare variant aggregate analysis implicates Ca2+-binding neuro-immunomodulator CALB2 in ulcerative colitis. Highly significant overall overlap of common variant risk for inflammatory bowel disease susceptibility between individuals with African and European ancestries was observed, with 41 of 241 previously known lead variants replicated and overall correlations in effect sizes of 0.68 for combined inflammatory bowel disease. Nevertheless, subtle differences influence the performance of polygenic risk scores, and we show that ancestry-appropriate weights significantly improve polygenic prediction in the highest percentiles of risk. The median amount of variance explained per locus remains the same in African and European cohorts, providing evidence for compensation of effect sizes as allele frequencies diverge, as expected under a highly polygenic model of disease.

Birth Cohort Colorectal Cancer (CRC): Implications for Research and Practice.

Colorectal cancer (CRC) epidemiology is changing due to a birth cohort effect, first recognized by increasing incidence of early onset CRC (EOCRC, age <50 years). In this paper, we define "birth cohort CRC" as the observed phenomenon, among individuals born 1960 and later, of increasing CRC risk across successive birth cohorts, rising EOCRC incidence, increasing incidence among individuals aged 50 to 54 years, and flattening of prior decreasing incidence among individuals aged 55 to 74 years. We demonstrate birth cohort CRC is associated with unique features, including increasing rectal cancer (greater than colon) and distant (greater than local) stage CRC diagnosis, and increasing EOCRC across all racial/ethnic groups. We review potential risk factors, etiologies, and mechanisms for birth cohort CRC, using EOCRC as a starting point and describing importance of viewing these through the lens of birth cohort. We also outline implications of birth cohort CRC for epidemiologic and translational research, as well as current clinical practice. We postulate that recognition of birth cohort CRC as an entity-including and extending beyond rising EOCRC-can advance understanding of risk factors, etiologies, and mechanisms, and address the public health consequences of changing CRC epidemiology.