A deep catalogue of protein-coding variation in 983,578 individuals.

Rare coding variants that significantly impact function provide insights into the biology of a gene1-3. However, ascertaining their frequency requires large sample sizes4-8. Here, we present a catalogue of human protein-coding variation, derived from exome sequencing of 983,578 individuals across diverse populations. 23% of the Regeneron Genetics Center Million Exome data (RGC-ME) comes from non-European individuals of African, East Asian, Indigenous American, Middle Eastern, and South Asian ancestry. This catalogue includes over 10.4 million missense and 1.1 million predicted loss-of-function (pLOF) variants. We identify individuals with rare biallelic pLOF variants in 4,848 genes, 1,751 of which have not been previously reported. From precise quantitative estimates of selection against heterozygous loss-of-function, we identify 3,988 loss-of-function intolerant genes, including 86 that were previously assessed as tolerant and 1,153 lacking established disease annotation. We also define regions of missense depletion at high resolution. Notably, 1,482 genes have regions depleted of missense variants despite being tolerant to pLOF variants. Finally, we estimate that 3% of individuals have a clinically actionable genetic variant, and that 11,773 variants reported in ClinVar with unknown significance are likely to be deleterious cryptic splice sites. To facilitate variant interpretation and genetics-informed precision medicine, we make this important resource of coding variation from the RGC-ME accessible via a public variant allele frequency browser.

Adjusting for principal components can induce spurious associations in genome-wide association studies in admixed populations.

Principal component analysis (PCA) is widely used to control for population structure in genome-wide association studies (GWAS). Top principal components (PCs) typically reflect population structure, but challenges arise in deciding how many PCs are needed and ensuring that PCs do not capture other artifacts such as regions with atypical linkage disequilibrium (LD). In response to the latter, many groups suggest performing LD pruning or excluding known high LD regions prior to PCA. However, these suggestions are not universally implemented and the implications for GWAS are not fully understood, especially in the context of admixed populations. In this paper, we investigate the impact of pre-processing and the number of PCs included in GWAS models in African American samples from the Women's Women's Health Initiative SNP Health Association Resource and two Trans-Omics for Precision Medicine Whole Genome Sequencing Project contributing studies (Jackson Heart Study and Genetic Epidemiology of Chronic Obstructive Pulmonary Disease Study). In all three samples, we find the first PC is highly correlated with genome-wide ancestry whereas later PCs often capture local genomic features. The pattern of which, and how many, genetic variants are highly correlated with individual PCs differs from what has been observed in prior studies focused on European populations and leads to distinct downstream consequences: adjusting for such PCs yields biased effect size estimates and elevated rates of spurious associations due to the phenomenon of collider bias. Excluding high LD regions identified in previous studies does not resolve these issues. LD pruning proves more effective, but the optimal choice of thresholds varies across datasets. Altogether, our work highlights unique issues that arise when using PCA to control for ancestral heterogeneity in admixed populations and demonstrates the importance of careful pre-processing and diagnostics to ensure that PCs capturing multiple local genomic features are not included in GWAS models.

Improving polygenic risk prediction in admixed populations by explicitly modeling ancestral-differential effects via GAUDI.

Polygenic risk scores (PRS) have shown successes in clinics, but most PRS methods focus only on participants with distinct primary continental ancestry without accommodating recently-admixed individuals with mosaic continental ancestry backgrounds for different segments of their genomes. Here, we develop GAUDI, a novel penalized-regression-based method specifically designed for admixed individuals. GAUDI explicitly models ancestry-differential effects while borrowing information across segments with shared ancestry in admixed genomes. We demonstrate marked advantages of GAUDI over other methods through comprehensive simulation and real data analyses for traits with associated variants exhibiting ancestral-differential effects. Leveraging data from the Women's Health Initiative study, we show that GAUDI improves PRS prediction of white blood cell count and C-reactive protein in African Americans by > 64% compared to alternative methods, and even outperforms PRS-CSx with large European GWAS for some scenarios. We believe GAUDI will be a valuable tool to mitigate disparities in PRS performance in admixed individuals.

Genotyping, sequencing and analysis of 140,000 adults from Mexico City.

The Mexico City Prospective Study is a prospective cohort of more than 150,000 adults recruited two decades ago from the urban districts of Coyoacán and Iztapalapa in Mexico City1. Here we generated genotype and exome-sequencing data for all individuals and whole-genome sequencing data for 9,950 selected individuals. We describe high levels of relatedness and substantial heterogeneity in ancestry composition across individuals. Most sequenced individuals had admixed Indigenous American, European and African ancestry, with extensive admixture from Indigenous populations in central, southern and southeastern Mexico. Indigenous Mexican segments of the genome had lower levels of coding variation but an excess of homozygous loss-of-function variants compared with segments of African and European origin. We estimated ancestry-specific allele frequencies at 142 million genomic variants, with an effective sample size of 91,856 for Indigenous Mexican ancestry at exome variants, all available through a public browser. Using whole-genome sequencing, we developed an imputation reference panel that outperforms existing panels at common variants in individuals with high proportions of central, southern and southeastern Indigenous Mexican ancestry. Our work illustrates the value of genetic studies in diverse populations and provides foundational imputation and allele frequency resources for future genetic studies in Mexico and in the United States, where the Hispanic/Latino population is predominantly of Mexican descent.

X-Chromosome Association Study in Latin American Cohorts Identifies New Loci in Parkinson's Disease.

BACKGROUND: Sex differences in Parkinson's disease (PD) risk are well-known. However, the role of sex chromosomes in the development and progression of PD is still unclear. OBJECTIVE: The objective of this study was to perform the first X-chromosome-wide association study for PD risk in a Latin American cohort. METHODS: We used data from three admixed cohorts: (1) Latin American Research consortium on the Genetics of Parkinson's Disease (n = 1504) as discover cohort, and (2) Latino cohort from International Parkinson Disease Genomics Consortium (n = 155) and (3) Bambui Aging cohort (n = 1442) as replication cohorts. We also developed an X-chromosome framework specifically designed for admixed populations. RESULTS: We identified eight linkage disequilibrium regions associated with PD. We replicated one of these regions (top variant rs525496; discovery odds ratio [95% confidence interval]: 0.60 [0.478-0.77], P = 3.13 × 10-5 replication odds ratio: 0.60 [0.37-0.98], P = 0.04). rs5525496 is associated with multiple expression quantitative trait loci in brain and non-brain tissues, including RAB9B, H2BFM, TSMB15B, and GLRA4, but colocalization analysis suggests that rs5525496 may not mediate risk by expression of these genes. We also replicated a previous X-chromosome-wide association study finding (rs28602900), showing that this variant is associated with PD in non-European populations. CONCLUSIONS: Our results reinforce the importance of including X-chromosome and diverse populations in genetic studies. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Admixture mapping implicates 13q33.3 as ancestry-of-origin locus for Alzheimer disease in Hispanic and Latino populations.

Alzheimer disease (AD) is the most common form of senile dementia, with high incidence late in life in many populations including Caribbean Hispanic (CH) populations. Such admixed populations, descended from more than one ancestral population, can present challenges for genetic studies, including limited sample sizes and unique analytical constraints. Therefore, CH populations and other admixed populations have not been well represented in studies of AD, and much of the genetic variation contributing to AD risk in these populations remains unknown. Here, we conduct genome-wide analysis of AD in multiplex CH families from the Alzheimer Disease Sequencing Project (ADSP). We developed, validated, and applied an implementation of a logistic mixed model for admixture mapping with binary traits that leverages genetic ancestry to identify ancestry-of-origin loci contributing to AD. We identified three loci on chromosome 13q33.3 associated with reduced risk of AD, where associations were driven by Native American (NAM) ancestry. This AD admixture mapping signal spans the FAM155A, ABHD13, TNFSF13B, LIG4, and MYO16 genes and was supported by evidence for association in an independent sample from the Alzheimer's Genetics in Argentina-Alzheimer Argentina consortium (AGA-ALZAR) study with considerable NAM ancestry. We also provide evidence of NAM haplotypes and key variants within 13q33.3 that segregate with AD in the ADSP whole-genome sequencing data. Interestingly, the widely used genome-wide association study approach failed to identify associations in this region. Our findings underscore the potential of leveraging genetic ancestry diversity in recently admixed populations to improve genetic mapping, in this case for AD-relevant loci.

A deep catalog of protein-coding variation in 985,830 individuals.

Coding variants that have significant impact on function can provide insights into the biology of a gene but are typically rare in the population. Identifying and ascertaining the frequency of such rare variants requires very large sample sizes. Here, we present the largest catalog of human protein-coding variation to date, derived from exome sequencing of 985,830 individuals of diverse ancestry to serve as a rich resource for studying rare coding variants. Individuals of African, Admixed American, East Asian, Middle Eastern, and South Asian ancestry account for 20% of this Exome dataset. Our catalog of variants includes approximately 10.5 million missense (54% novel) and 1.1 million predicted loss-of-function (pLOF) variants (65% novel, 53% observed only once). We identified individuals with rare homozygous pLOF variants in 4,874 genes, and for 1,838 of these this work is the first to document at least one pLOF homozygote. Additional insights from the RGC-ME dataset include 1) improved estimates of selection against heterozygous loss-of-function and identification of 3,459 genes intolerant to loss-of-function, 83 of which were previously assessed as tolerant to loss-of-function and 1,241 that lack disease annotations; 2) identification of regions depleted of missense variation in 457 genes that are tolerant to loss-of-function; 3) functional interpretation for 10,708 variants of unknown or conflicting significance reported in ClinVar as cryptic splice sites using splicing score thresholds based on empirical variant deleteriousness scores derived from RGC-ME; and 4) an observation that approximately 3% of sequenced individuals carry a clinically actionable genetic variant in the ACMG SF 3.1 list of genes. We make this important resource of coding variation available to the public through a variant allele frequency browser. We anticipate that this report and the RGC-ME dataset will serve as a valuable reference for understanding rare coding variation and help advance precision medicine efforts.

X-Chromosome Association Study in Latin American Cohorts Identifies New Loci in Parkinson Disease.

Sex differences in Parkinson Disease (PD) risk are well-known. However, it is still unclear the role of sex chromosomes in the development and progression of PD. We performed the first X-chromosome Wide Association Study (XWAS) for PD risk in Latin American individuals. We used data from three admixed cohorts: (i) Latin American Research consortium on the GEnetics of Parkinson's Disease (n=1,504) as discover cohort and (ii) Latino cohort from International Parkinson Disease Genomics Consortium (n = 155) and (iii) Bambui Aging cohort (n= 1,442) as replication cohorts. After developing a X-chromosome framework specifically designed for admixed populations, we identified eight linkage disequilibrium regions associated with PD. We fully replicated one of these regions (top variant rs525496; discovery OR [95%CI]: 0.60 [0.478 - 0.77], p = 3.13 × 10 -5 ; replication OR: 0.60 [0.37-0.98], p = 0.04). rs525496 is an expression quantitative trait loci for several genes expressed in brain tissues, including RAB9B, H2BFM, TSMB15B and GLRA4 . We also replicated a previous XWAS finding (rs28602900), showing that this variant is associated with PD in non-European populations. Our results reinforce the importance of including X-chromosome and diverse populations in genetic studies.

Association of African Ancestry-Specific APOE Missense Variant R145C With Risk of Alzheimer Disease.

Importance: Numerous studies have established the association of the common APOE ε2 and APOE ε4 alleles with Alzheimer disease (AD) risk across ancestries. Studies of the interaction of these alleles with other amino acid changes on APOE in non-European ancestries are lacking and may improve ancestry-specific risk prediction. Objective: To determine whether APOE amino acid changes specific to individuals of African ancestry modulate AD risk. Design, Setting, and Participants: Case-control study including 31 929 participants and using a sequenced discovery sample (Alzheimer Disease Sequencing Project; stage 1) followed by 2 microarray imputed data sets derived from the Alzheimer Disease Genetic Consortium (stage 2, internal replication) and the Million Veteran Program (stage 3, external validation). This study combined case-control, family-based, population-based, and longitudinal AD cohorts, which recruited participants (1991-2022) in primarily US-based studies with 1 US/Nigerian study. Across all stages, individuals included in this study were of African ancestry. Exposures: Two APOE missense variants (R145C and R150H) were assessed, stratified by APOE genotype. Main Outcomes and Measures: The primary outcome was AD case-control status, and secondary outcomes included age at AD onset. Results: Stage 1 included 2888 cases (median age, 77 [IQR, 71-83] years; 31.3% male) and 4957 controls (median age, 77 [IQR, 71-83] years; 28.0% male). In stage 2, across multiple cohorts, 1201 cases (median age, 75 [IQR, 69-81] years; 30.8% male) and 2744 controls (median age, 80 [IQR, 75-84] years; 31.4% male) were included. In stage 3, 733 cases (median age, 79.4 [IQR, 73.8-86.5] years; 97.0% male) and 19 406 controls (median age, 71.9 [IQR, 68.4-75.8] years; 94.5% male) were included. In ε3/ε4-stratified analyses of stage 1, R145C was present in 52 individuals with AD (4.8%) and 19 controls (1.5%); R145C was associated with an increased risk of AD (odds ratio [OR], 3.01; 95% CI, 1.87-4.85; P = 6.0 × 10-6) and was associated with a reported younger age at AD onset (ß, -5.87 years; 95% CI, -8.35 to -3.4 years; P = 3.4 × 10-6). Association with increased AD risk was replicated in stage 2 (R145C was present in 23 individuals with AD [4.7%] and 21 controls [2.7%]; OR, 2.20; 95% CI, 1.04-4.65; P = .04) and was concordant in stage 3 (R145C was present in 11 individuals with AD [3.8%] and 149 controls [2.7%]; OR, 1.90; 95% CI, 0.99-3.64; P = .051). Association with earlier AD onset was replicated in stage 2 (ß, -5.23 years; 95% CI, -9.58 to -0.87 years; P = .02) and stage 3 (ß, -10.15 years; 95% CI, -15.66 to -4.64 years; P = 4.0 × 10-4). No significant associations were observed in other APOE strata for R145C or in any APOE strata for R150H. Conclusions and Relevance: In this exploratory analysis, the APOE ε3[R145C] missense variant was associated with an increased risk of AD among individuals of African ancestry with the ε3/ε4 genotype. With additional external validation, these findings may inform AD genetic risk assessment in individuals of African ancestry.

Polygenic risk prediction and SNCA haplotype analysis in a Latino Parkinson's disease cohort.

BACKGROUND: Large-scale Parkinson's disease (PD) genome-wide association studies (GWAS) have, until recently, only been conducted on subjects with European-ancestry. Consequently, polygenic risk scores (PRS) constructed using PD GWAS data are likely to be less predictive when applied to non-European cohorts. METHODS: Using GWAS data from the largest study to date, we constructed a PD PRS for a Latino PD cohort (1497 subjects from LARGE-PD) and tested it for association with PD status and age at onset. We validated the PRS performance by testing it in an independent Latino cohort (448 subjects) and by repeating the analysis in LARGE-PD with the addition of 440 external Peruvian controls. We also tested SNCA haplotypes for association with PD risk in LARGE-PD and a European-ancestry PD cohort. RESULTS: The GWAS-significant PD PRS had an area under the receiver-operator curve (AUC) of 0.668 (95% CI: 0.640-0.695) in LARGE-PD. The inclusion of external Peruvian controls mitigated this result, dropping the AUC 0.632 (95% CI: 0.607-0.657). At the SNCA locus, haplotypes differ by ancestry. Ancestry-specific SNCA haplotypes were associated with PD status in both LARGE-PD and the European-ancestry cohort (p-value < 0.05). These haplotypes both include the rs356182 G-allele, but only share 14% of their variants overall. CONCLUSION: The PD PRS has potential for PD risk prediction in Latinos, but variability caused by admixture patterns and bias in a European-ancestry PD PRS data limits its utility. The inclusion of diverse subjects can help elucidate PD risk loci and improve risk prediction in non-European cohorts.

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.

Protein prediction for trait mapping in diverse populations.

Genetically regulated gene expression has helped elucidate the biological mechanisms underlying complex traits. Improved high-throughput technology allows similar interrogation of the genetically regulated proteome for understanding complex trait mechanisms. Here, we used the Trans-omics for Precision Medicine (TOPMed) Multi-omics pilot study, which comprises data from Multi-Ethnic Study of Atherosclerosis (MESA), to optimize genetic predictors of the plasma proteome for genetically regulated proteome-wide association studies (PWAS) in diverse populations. We built predictive models for protein abundances using data collected in TOPMed MESA, for which we have measured 1,305 proteins by a SOMAscan assay. We compared predictive models built via elastic net regression to models integrating posterior inclusion probabilities estimated by fine-mapping SNPs prior to elastic net. In order to investigate the transferability of predictive models across ancestries, we built protein prediction models in all four of the TOPMed MESA populations, African American (n = 183), Chinese (n = 71), European (n = 416), and Hispanic/Latino (n = 301), as well as in all populations combined. As expected, fine-mapping produced more significant protein prediction models, especially in African ancestries populations, potentially increasing opportunity for discovery. When we tested our TOPMed MESA models in the independent European INTERVAL study, fine-mapping improved cross-ancestries prediction for some proteins. Using GWAS summary statistics from the Population Architecture using Genomics and Epidemiology (PAGE) study, which comprises ∼50,000 Hispanic/Latinos, African Americans, Asians, Native Hawaiians, and Native Americans, we applied S-PrediXcan to perform PWAS for 28 complex traits. The most protein-trait associations were discovered, colocalized, and replicated in large independent GWAS using proteome prediction model training populations with similar ancestries to PAGE. At current training population sample sizes, performance between baseline and fine-mapped protein prediction models in PWAS was similar, highlighting the utility of elastic net. Our predictive models in diverse populations are publicly available for use in proteome mapping methods at https://doi.org/10.5281/zenodo.4837327.

Associating sleep problems with advanced cancer diagnosis, and immune checkpoint treatment outcomes: a pilot study.

BACKGROUND: Sleep problems (SP) are common in cancer patients but have not been previously assessed in patients receiving immune checkpoint inhibitors (ICI). METHODS: We collected questionnaire data on sleep apnea risk, insomnia, and general sleep patterns. We used an adjusted multivariate Poisson regression to calculate prevalence ratios (PRs) and associated 95% confidence intervals (CIs) for associations between these SP and metastatic versus localized cancer stage (M1 vs. M0), and adjusted logistic regression models to calculate ORs for associations between SP with the number of ICI infusions completed (6 + vs. < 6). RESULTS: Among 32 patients who received ICI treatment, the prevalence of low, intermediate, and high-risk OSA risk was 36%, 42%, and 21%, respectively. Overall, 58% of participants reported clinically significant insomnia. We did not find a significant association between intermediate or high risk OSA (vs. low risk) and metastatic cancer status (PR = 1.01 (95% CI: 0.28, 3.67)). Patients in the cohort who reported taking > 15 min to fall asleep were 3.6 times more likely to be diagnosed with metastatic cancer compared to those reporting shorter sleep latency (95% CI (1.74, 7.35)). We did not find a significant association between SP and number of ICI infusions completed. CONCLUSION: Our data associating sleep apnea risk, insomnia, and sleep patterns with more advanced cancer encourages further exploration in larger-scale observational studies and suggests interventional clinical trials focused on sleep quality improvement that could result in better outcomes for these patients.

Maternal-fetal genetic interactions, imprinting, and risk of placental abruption.

RESULTS: Abruption cases were more likely to experience preeclampsia, have shorter gestational age, and deliver infants with lower birthweight compared with controls. Models with MFGI effects provided improved fit than models with only maternal and fetal genotype main effects for SNP rs12530904 (p-value = 1.2e-04) in calcium/calmodulin-dependent protein kinase [CaM kinase] II beta (CAMK2B), and, SNP rs73136795 (p-value = 1.9e-04) in peroxisome proliferator-activated receptor-gamma (PPARG), both MB genes. We identified 320 SNPs in 45 maternally-imprinted genes (including potassium voltage-gated channel subfamily Q member 1 [KCNQ1], neurotrimin [NTM], and, ATPase phospholipid transporting 10 A [ATP10A]) associated with abruption. Top hits included rs2012323 (p-value = 1.6E-16) and rs12221520 (p-value1.3e-13) in KCNQ1, rs8036892 (p-value = 9.3E-17) and rs188497582 in ATP10A, rs12589854 (p-value = 2.9E-11) and rs80203467 (p-value = 4.6e-11) in maternally expressed 8, small nucleolar RNA host (MEG8), and rs138281088 in solute carrier family 22 member 2 (SLC22A2) (p-value = 6.8e-9). CONCLUSIONS: We identified novel PA-related maternal-fetal MB gene interactions and imprinting effects that highlight the role of the fetus in PA risk development. Findings can inform mechanistic investigations to understand the pathogenesis of PA.

Genome-Wide Admixture Mapping of Estimated Glomerular Filtration Rate and Chronic Kidney Disease Identifies European and African Ancestry-of-Origin Loci in Hispanic and Latino Individuals in the United States.

BACKGROUND: Admixture mapping is a powerful approach for gene mapping of complex traits that leverages the diverse genetic ancestry in populations with recent admixture, such as Hispanic or Latino individuals in the United States. These individuals have an increased risk of CKD. METHODS: We performed genome-wide admixture mapping for both CKD and eGFR in a sample of 12,601 participants from the Hispanic Community Health Study/Study of Latinos, with validation in a sample of 8191 Black participants from the Women's Health Initiative (WHI). We also compared the findings with those from a conventional genome-wide association study. RESULTS: Three novel ancestry-of-origin loci were identified on chromosomes 2, 14, and 15 for CKD and eGFR. The chromosome 2 locus comprises two European ancestry regions encompassing the FSHR and NRXN1 genes, with European ancestry at this locus associated with increased CKD risk. The chromosome 14 locus, found within the DLK1-DIO3 imprinted domain, was associated with lower eGFR and driven by European ancestry. The eGFR-associated locus on chromosome 15 included intronic variants of RYR3 and was within an African-specific genomic region associated with higher eGFR. The genome-wide association study failed to identify significant associations in these regions. We validated the chromosome 14 and 15 loci associated with eGFR in the WHI Black participants. CONCLUSIONS: This study provides evidence of shared ancestry-specific genomic regions influencing eGFR in Hispanic or Latino individuals and Black individuals and illustrates the potential for leveraging genetic ancestry in recently admixed populations for the discovery of novel candidate loci for kidney phenotypes.

Sleep problems and risk of cancer incidence and mortality in an older cohort: The Cardiovascular Health Study (CHS).

BACKGROUND: Sleep problems (SP) can indicate underlying sleep disorders, such as obstructive sleep apnea, which may adversely impact cancer risk and mortality. METHODS: We assessed the association of baseline and longitudinal sleep apnea and insomnia symptoms with incident cancer (N = 3930) and cancer mortality (N = 4580) in the Cardiovascular Health Study. We used Cox proportional hazards regression to calculate adjusted hazard ratios (HR) and 95% confidence intervals (CI) to evaluate the associations. RESULTS: Overall, 885 incident cancers and 804 cancer deaths were identified over a median follow-up of 12 and 14 years, respectively. Compared to participants who reported no sleep apnea symptoms, the risk of incident cancer was inversely associated [(HR (95%CI)] with snoring [0.84 (0.71, 0.99)]. We noted an elevated prostate cancer incidence for apnea [2.34 (1.32, 4.15)] and snoring [1.69 (1.11, 2.57)]. We also noted an elevated HR for lymphatic or hematopoietic cancers [daytime sleepiness: 1.81 (1.06, 3.08)]. We found an inverse relationship for cancer mortality with respect to snoring [0.73 (0.62, 0.8)] and apnea [(0.69 (0.51, 0.94))]. We noted a significant inverse relationship between difficulty falling asleep and colorectal cancer death [0.32 (0.15, 0.69)] and snoring with lung cancer death [0.56 (0.35, 0.89)]. CONCLUSIONS: The relationship between SP and cancer risk and mortality was heterogeneous. Larger prospective studies addressing more cancer sites, molecular type-specific associations, and better longitudinal SP assessments are needed for improved delineation of SP-cancer risk dyad.

REHE: Fast variance components estimation for linear mixed models.

Linear mixed models are widely used in ecological and biological applications, especially in genetic studies. Reliable estimation of variance components is crucial for using linear mixed models. However, standard methods, such as the restricted maximum likelihood (REML), are computationally inefficient in large samples and may be unstable with small samples. Other commonly used methods, such as the Haseman-Elston (HE) regression, may yield negative estimates of variances. Utilizing regularized estimation strategies, we propose the restricted Haseman-Elston (REHE) regression and REHE with resampling (reREHE) estimators, along with an inference framework for REHE, as fast and robust alternatives that provide nonnegative estimates with comparable accuracy to REML. The merits of REHE are illustrated using real data and benchmark simulation studies.

Soluble Urokinase Plasminogen Activator Receptor: Genetic Variation and Cardiovascular Disease Risk in Black Adults.

BACKGROUND: suPAR (Soluble urokinase plasminogen activator receptor) has emerged as an important biomarker of coagulation, inflammation, and cardiovascular disease (CVD) risk. The contribution of suPAR to CVD risk and its genetic influence in Black populations have not been evaluated. METHODS: We measured suPAR in 3492 Black adults from the prospective, community-based JHS (Jackson Heart Study). Cross-sectional associations of suPAR with lifestyle and CVD risk factors were assessed, whole-genome sequence data were used to evaluate genetic associations of suPAR, and relationships of suPAR with incident CVD outcomes and overall mortality were estimated over follow-up. RESULTS: In Cox models adjusted for traditional CVD risk factors, estimated glomerular filtration rate, and CRP (C-reactive protein), each 1-SD higher suPAR was associated with a 21% to 31% increased risk of incident coronary heart disease, heart failure, stroke, and mortality. In the genome-wide association study, 2 missense (rs399145 encoding p.Thr86Ala, rs4760 encoding p.Phe272Leu) and 2 noncoding regulatory variants (rs73935023 within an enhancer element and rs4251805 within the promoter) of PLAUR on chromosome 19 were each independently associated with suPAR and together explained 14% of suPAR phenotypic variation. The allele frequencies of each of the four suPAR-associated genetic variants differ considerably across African and European populations. We further show that PLAUR rs73935023 can alter transcriptional activity in vitro. We did not find any association between genetically determined suPAR and CVD in JHS or a larger electronic medical record-based analyses of Blacks or Whites. CONCLUSIONS: Our results demonstrate the importance of ancestry-differentiated genetic variation on suPAR levels and indicate suPAR is a CVD biomarker in Black adults.

Nicotine metabolism and its association with CYP2A6 genotype among Indigenous people in Alaska who smoke.

Prevalence of smoking is higher in Alaska Native and American Indian (ANAI) populations living in Alaska than the general US population. Genetic factors contribute to smoking and cessation rates. The objective of this study was to compare CYP2A6 genetic variation and CYP2A6 enzyme activity toward nicotine in an ANAI population. ANAI (N = 151) people trying to quit smoking were recruited. DNA samples were genotyped for CYP2A6 variants *1X2A, *1B, *2, *4, *9, *10, *12, and *35. Multiple nicotine metabolites were measured in plasma and urine samples, including cotinine and 3'-hydroxycotinine used to determine CYP2A6 activity (e.g., nicotine metabolite ratio [NMR]). We calculated summary statistics for all of the genotypes and metabolites and assigned CYP2A6 activity scores based on known information. We studied the association of CYP2A6 variants with the NMR and smoking histories. The overall frequency of the CYP2A6*1B gain of function allele was high in the ANAI versus non-ANAI populations in other studies. Both *4 null and *9 decrease of function alleles had frequencies similar to previous studies of ANAI populations. In a multivariate analysis, the genotype-inferred CYP2A6 activity score was associated with both plasma and urine NMR (p value = 8.56E-08 and 4.08E-13, respectively). Plasma NMR was also associated with duration of smoking (p value < 0.01) but not urinary total nicotine equivalents uncorrected for creatinine (TNE9uc ) or biological sex. Urine NMR was significantly associated (p value < 0.01) with TNE9uc . Variation in NMR in this ANAI population is explained in part by CYP2A6 genetic variation.