Admixture mapping identifies novel loci for obstructive sleep apnea in Hispanic/Latino Americans

Advancements in genetic research by the Hispanic Community Health Study/Study of Latinos: A 10-year retrospective review

The Hispanic Community Health Study/Study of Latinos (HCHS/SOL) is a multicenter, longitudinal cohort study designed to evaluate environmental, lifestyle, and genetic risk factors as they relate to cardiometabolic and other chronic diseases among Hispanic/Latino populations in the United States. Since the study's inception in 2008, as a result of the study's robust genetic measures, HCHS/SOL has facilitated major contributions to the field of genetic research. This 10-year retrospective review highlights the major findings for genotype-phenotype relationships and advancements in statistical methods owing to the HCHS/SOL. Furthermore, we discuss the ethical and societal challenges of genetic research, especially among Hispanic/Latino adults in the United States. Continued genetic research, ancillary study expansion, and consortia collaboration through HCHS/SOL will further drive knowledge and advancements in human genetics research.

The Importance of Genetic Background and Neurotransmission in the Pathogenesis of the Co-Occurrence of Sleep Bruxism and Sleep-Disordered Breathing-Review of a New Perspective

Sleep bruxism (SB) and sleep-disordered breathing (SDB) are two prevalent conditions that significantly impact overall health. Studies suggest that up to 49.7% of individuals with SDB also exhibit symptoms of SB. This review aims to provide a comprehensive analysis of the role of genetic background and neurotransmission in the pathogenesis of the co-occurrence of SB and SDB. It seeks to synthesize current knowledge, highlight gaps in the existing literature, and propose a new perspective that integrates genetic and neurobiological factors. This review shows that both SB and SDB may be influenced by a combination of genetic, neurochemical, and environmental factors that contribute to their shared pathophysiology. The key neurotransmitters-dopamine, serotonin, and GABA-may play a significant role in their co-occurrence by regulating motor activity, sleep architecture, and respiratory control. Understanding genetic and neurochemical mechanisms may allow for more precise diagnostic tools and more personalized treatment approaches regarding SB and SDB. Clinically, there is a need for interdisciplinary collaboration between sleep specialists, dentists, neurologists, and geneticists. There is also a need to conduct large-scale genetic studies, coupled with neuroimaging and neurophysiological research, uncovering additional insights into the shared mechanisms of SB and SDB.

Lipid metabolism and neuromuscular junction as common pathways underlying the genetic basis of erectile dysfunction and obstructive sleep apnea

Erectile dysfunction (ED) incidence is higher in patients with obstructive sleep apnea (OSA). Studies have suggested that ED and OSA may activate similar pathways; however, few have investigated the links between their underlying genotypic profiles. Therefore, we conducted an in-silico analysis to test whether ED and OSA share genetic variants of risk and to identify any molecular, cellular and biological interactions between them. Two gene lists were manually curated through a literature review based on a PUBMED search, which resulted in one gene list associated with ED (total of 205 genes) and the other with OSA (total of 2622 genes). Between those gene sets, 35 were common for both lists (Fisher exact test, p-value = 0.027). The Protein-protein interaction (PPI) analysis using the intersect list as input showed that 3 of them had direct interactions (LPL, DGKB and PLCB1). In addition, the biological function of the genes contained in the intersect list suggested that pathways related to lipid metabolism and the neuromuscular junction were commonly found in the genetic basis of ED and OSA. From the shared genes between both conditions, the biological pathways highlighted in this study may serve as preliminary findings for future functional investigations on OSA and ED association.

UGT1A1*28 polymorphism and the risk of toxicity and disease progression in patients with breast cancer receiving sacituzumab govitecan

BACKGROUND

Sacituzumab govitecan (sacituzumab) emerged as an important agent in metastatic and locally recurrent HER2-negative breast cancer treatment. UGT1A1 polymorphisms have also been shown to predict sacituzumab toxicity.

METHODS

In this retrospective study, we sought to evaluate the associations between UGT1A1 status, toxicity, and therapeutic outcomes in sacituzumab recipients with advanced breast cancer who underwent genotype testing for UGT1A1 alleles (N = 68).

RESULTS

We found 17 (25%) of our patients to be homozygous for UGT1A1*28 and 24 (35.3%) were heterozygous. Of seven African American patients with triple-negative breast cancer, five were homozygous for UGT1A1*28 and two were heterozygous. Patients with a homozygous UGT1A1*28 genotype were significantly more likely to have treatment terminated because of adverse effects. However, the polymorphism was not associated with treatment discontinuation because of disease progression.

CONCLUSION

This retrospective, real-world analysis suggests potential clinical utility in UGT1A1 testing for patients receiving sacituzumab, but future trials are needed to confirm the association between genotypes and treatment outcomes.

Exploring the Shared Genetic Architecture Between Obstructive Sleep Apnea and Body Mass Index

Purpose

The reciprocal comorbidity of obstructive sleep apnea (OSA) and body mass index (BMI) has been observed, yet the shared genetic architecture between them remains unclear. This study aimed to explore the genetic overlaps between them.

Methods

Summary statistics were acquired from the genome-wide association studies (GWASs) on OSA (Ncase = 41,704; Ncontrol = 335,573) and BMI (Noverall = 461,460). A comprehensive genome-wide cross-trait analysis was performed to quantify global and local genetic correlation, infer the bidirectional causal relationships, detect independent pleiotropic loci, and investigate potential comorbid genes.

Results

A positive significant global genetic correlation between OSA and BMI was observed (r g = 0.52, P = 2.85e-122), which was supported by three local signal. The Mendelian randomization analysis confirmed bidirectional causal associations. In the meta-analysis of cross-traits GWAS, a total of 151 single-nucleotide polymorphisms were found to be pleiotropic between OSA and BMI. Additionally, we discovered that the genetic association between OSA and BMI is concentrated in 12 brain regions. Finally, a total 134 expression-tissue pairs were observed to have a significant impact on both OSA and BMI within the specified brain regions.

Conclusion

Our comprehensive genome-wide cross-trait analysis indicates a shared genetic architecture between OSA and BMI, offering new perspectives on the possible mechanisms involved.

Association of Sleep Pattern and Genetic Susceptibility with Obstructive Sleep Apnea: A Prospective Analysis of the UK Biobank

Purpose

The prevalence of obstructive sleep apnea (OSA) is high worldwide. This study aimed to quantify the relationship between the incidence of OSA and sleep patterns and genetic susceptibility.

Methods

A total of 355,133 white British participants enrolled in the UK Biobank between 2006 and 2010 with follow-up data until September 2021 were recruited. We evaluated sleep patterns using a customized sleep scoring method based on the low-risk sleep phenotype, defined as follows: morning chronotype, 7-8 hours of sleep per day, never/rarely experience insomnia, no snoring, no frequent daytime sleepiness, never/rarely nap, and easily getting up early. The polygenic risk score was calculated to assess genetic susceptibility to OSA. Cox proportional hazard models were used to evaluate the associations between OSA and sleep patterns and genetic susceptibility.

Results

During a mean follow-up of 12.57 years, 4618 participants were diagnosed with OSA (age: 56.83 ± 7.69 years, women: 31.3%). Compared with those with a poor sleep pattern, participants with a normal (HR: 0.42, 95% CI: 0.38-0.46), ideal (HR: 0.21, 95% CI: 0.19-0.24), or optimal (HR: 0.15, 95% CI: 0.12-0.18) sleep pattern were significantly more likely to have OSA. The genetic susceptibility of 173,239 participants was calculated, and the results showed that poor (HR: 3.67, 95% CI: 2.95-4.57) and normal (HR: 1.89, 95% CI: 1.66-2.16) sleep patterns with high genetic susceptibility can increase the risk for OSA.

Conclusion

This large-scale prospective study provides evidence suggesting that sleep patterns across seven low-risk sleep phenotypes may protect against OSA in individuals with varying degrees of genetic susceptibility.

Waking Up the Sleep Field: An Overview on the Implications of Genetics and Bioinformatics of Sleep

Sleep genetics is an intriguing, as yet less understood, understudied, emerging area of biological and medical discipline. A generalist may not be aware of the current status of the field given the variety of journals that have published studies on the genetics of sleep and the circadian clock over the years. For researchers venturing into this fascinating area, this review thus includes fundamental features of circadian rhythm and genetic variables impacting sleep-wake cycles. Sleep/wake pathway medication exposure and susceptibility are influenced by genetic variations, and the responsiveness of sleep-related medicines is influenced by several functional polymorphisms. This review highlights the features of the circadian timing system and then a genetic perspective on wakefulness and sleep, as well as the relationship between sleep genetics and sleep disorders. Neurotransmission genes, as well as circadian and sleep/wake receptors, exhibit functional variability. Experiments on animals and humans have shown that these genetic variants impact clock systems, signaling pathways, nature, amount, duration, type, intensity, quality, and quantity of sleep. In this regard, the overview covers research on sleep genetics, the genomic properties of several popular model species used in sleep studies, homologs of mammalian genes, sleep disorders, and related genes. In addition, the study includes a brief discussion of sleep, narcolepsy, and restless legs syndrome from the viewpoint of a model organism. It is suggested that the understanding of genetic clues on sleep function and sleep disorders may, in future, result in an evidence-based, personalized treatment of sleep disorders.

Sleep regulation and host genetics

Due to the multifactorial and complex nature of rest, we focus on phenotypes related to sleep. Sleep regulation is a multifactorial process. In this chapter, we focus on those phenotypes inherent to sleep that are highly prevalent in the population, and that can be modulated by lifestyle, such as sleep quality and duration, insomnia, restless leg syndrome and daytime sleepiness. We, therefore, leave in the background those phenotypes that constitute infrequent pathologies or for which the current level of scientific evidence does not favour the implementation of practical approaches of this type. Similarly, the regulation of sleep quality is intimately linked to the regulation of the circadian rhythm. Although this relationship is discussed in the sections that require it, the in-depth study of circadian rhythm regulation at the molecular level deserves a separate chapter, and this is how it is dealt with in this volume.

Update on the genetic basis of obstructive sleep apnoea - hype or hope?

PURPOSE OF REVIEW

The obstructive sleep apnoea syndrome (OSAS) is a chronic, common condition in western societies which can lead to adverse cardiometabolic effects if left untreated and is one of the commonest causes of excessive daytime somnolence.

RECENT FINDINGS

The presentation of OSAS is diverse and is thought to comprise of different intermediate phenotypes and endotypes in varying proportions in each individual. Unfortunately, due to its heterogeneity and the changing definitions of the disorder by workers in the field, attempts at revealing the genetic basis of OSAS has been fraught with difficulty.

SUMMARY

This brief review presents a short update on the achievements of the past three decades in this understudied and underfunded area of endeavour in respiratory sleep medicine. The genetic underpinnings of OSAS remain elusive.

Ancestry-driven metabolite variation provides insights into disease states in admixed populations

BACKGROUND

Metabolic pathways are related to physiological functions and disease states and are influenced by genetic variation and environmental factors. Hispanics/Latino individuals have ancestry-derived genomic regions (local ancestry) from their recent admixture that have been less characterized for associations with metabolite abundance and disease risk.

METHODS

We performed admixture mapping of 640 circulating metabolites in 3887 Hispanic/Latino individuals from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Metabolites were quantified in fasting serum through non-targeted mass spectrometry (MS) analysis using ultra-performance liquid chromatography-MS/MS. Replication was performed in 1856 nonoverlapping HCHS/SOL participants with metabolomic data.

RESULTS

By leveraging local ancestry, this study identified significant ancestry-enriched associations for 78 circulating metabolites at 484 independent regions, including 116 novel metabolite-genomic region associations that replicated in an independent sample. Among the main findings, we identified Native American enriched genomic regions at chromosomes 11 and 15, mapping to FADS1/FADS2 and LIPC, respectively, associated with reduced long-chain polyunsaturated fatty acid metabolites implicated in metabolic and inflammatory pathways. An African-derived genomic region at chromosome 2 was associated with N-acetylated amino acid metabolites. This region, mapped to ALMS1, is associated with chronic kidney disease, a disease that disproportionately burdens individuals of African descent.

CONCLUSIONS

Our findings provide important insights into differences in metabolite quantities related to ancestry in admixed populations including metabolites related to regulation of lipid polyunsaturated fatty acids and N-acetylated amino acids, which may have implications for common diseases in populations.

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.

International Consensus Statement on Obstructive Sleep Apnea

BACKGROUND

Evaluation and interpretation of the literature on obstructive sleep apnea (OSA) allows for consolidation and determination of the key factors important for clinical management of the adult OSA patient. Toward this goal, an international collaborative of multidisciplinary experts in sleep apnea evaluation and treatment have produced the International Consensus statement on Obstructive Sleep Apnea (ICS:OSA).

METHODS

Using previously defined methodology, focal topics in OSA were assigned as literature review (LR), evidence-based review (EBR), or evidence-based review with recommendations (EBR-R) formats. Each topic incorporated the available and relevant evidence which was summarized and graded on study quality. Each topic and section underwent iterative review and the ICS:OSA was created and reviewed by all authors for consensus.

RESULTS

The ICS:OSA addresses OSA syndrome definitions, pathophysiology, epidemiology, risk factors for disease, screening methods, diagnostic testing types, multiple treatment modalities, and effects of OSA treatment on multiple OSA-associated comorbidities. Specific focus on outcomes with positive airway pressure (PAP) and surgical treatments were evaluated.

CONCLUSION

This review of the literature consolidates the available knowledge and identifies the limitations of the current evidence on OSA. This effort aims to create a resource for OSA evidence-based practice and identify future research needs. Knowledge gaps and research opportunities include improving the metrics of OSA disease, determining the optimal OSA screening paradigms, developing strategies for PAP adherence and longitudinal care, enhancing selection of PAP alternatives and surgery, understanding health risk outcomes, and translating evidence into individualized approaches to therapy.

Whole-exome identifies germline variants in families with obstructive sleep apnea syndrome

Background: Obstructive sleep apnea syndrome (OSAS) (OMIM #107650) is characterized by complete or partial obstruction of the upper airways, resulting in periods of sleep associated apnea. OSAS increases morbidity and mortality risk from cardiovascular and cerebrovascular diseases. While heritability of OSAS is estimated at ∼40%, the precise underlying genes remain elusive. Brazilian families with OSAS that follows as seemingly autosomal dominant inheritance pattern were recruited. Methods: The study included nine individuals from two Brazilian families displaying a seemingly autosomal dominant inheritance pattern of OSAS. Whole exome sequencing of germline DNA were analyzed using Mendel, MD software. Variants selected were analyzed using Varstation^® with subsequent analyses that included validation by Sanger sequencing, pathogenic score assessment by ACMG criteria, co-segregation analyses (when possible) allele frequency, tissue expression patterns, pathway analyses, effect on protein folding modeling using Swiss-Model and RaptorX. Results: Two families (six affected patients and three unaffected controls) were analyzed. A comprehensive multistep analysis yielded variants in COX20 (rs946982087) (family A), PTPDC1 (rs61743388) and TMOD4 (rs141507115) (family B) that seemed to be strong candidate genes for being OSAS associated genes in these families. Conclusion: Sequence variants in COX20, PTPDC1 and TMOD4 seemingly are associated with OSAS phenotype in these families. Further studies in more, ethnically diverse families and non-familial OSAS cases are needed to better define the role of these variants as contributors to OSAS phenotype.

Evolving Science on Cardiovascular Disease Among Hispanic/Latino Adults: JACC International

The landmark, multicenter HCHS/SOL (Hispanic Community Health Study/Study of Latinos) is the largest, most comprehensive, longitudinal community-based cohort study to date of diverse Hispanic/Latino persons in the United States. The HCHS/SOL aimed to address the dearth of comprehensive data on risk factors for cardiovascular disease (CVD) and other chronic diseases in this population and has expanded considerably in scope since its inception. This paper describes the aims/objectives and data collection of the HCHS/SOL and its ancillary studies to date and highlights the critical and sizable contributions made by the study to understanding the prevalence of and changes in CVD risk/protective factors and the burden of CVD and related chronic conditions among adults of diverse Hispanic/Latino backgrounds. The continued follow-up of this cohort will allow in-depth investigations on cardiovascular and pulmonary outcomes in this population, and data from the ongoing ancillary studies will facilitate generation of new hypotheses and study questions.

Genome-wide association study of obstructive sleep apnoea in the Million Veteran Program uncovers genetic heterogeneity by sex

BACKGROUND

Genome-wide association studies (GWAS) for obstructive sleep apnoea (OSA) are limited due to the underdiagnosis of OSA, leading to misclassification of OSA, which consequently reduces statistical power. We performed a GWAS of OSA in the Million Veteran Program (MVP) of the U.S. Department of Veterans Affairs (VA) healthcare system, where OSA prevalence is close to its true population prevalence.

METHODS

We performed GWAS of 568,576 MVP participants, stratified by biological sex and by harmonized race/ethnicity and genetic ancestry (HARE) groups of White, Black, Hispanic, and Asian individuals. We considered both BMI adjusted (BMI-adj) and unadjusted (BMI-unadj) models. We replicated associations in independent datasets, and analysed the heterogeneity of OSA genetic associations across HARE and sex groups. We finally performed a larger meta-analysis GWAS of MVP, FinnGen, and the MGB Biobank, totalling 916,696 individuals.

FINDINGS

MVP participants are 91% male. OSA prevalence is 21%. In MVP there were 18 and 6 genome-wide significant loci in BMI-unadj and BMI-adj analyses, respectively, corresponding to 21 association regions. Of these, 17 were not previously reported in association with OSA, and 13 replicated in FinnGen (False Discovery Rate p-value < 0.05). There were widespread significant differences in genetic effects between men and women, but less so across HARE groups. Meta-analysis of MVP, FinnGen, and MGB biobank revealed 17 additional, previously unreported, genome-wide significant regions.

INTERPRETATION

Sex differences in genetic associations with OSA are widespread, likely associated with multiple OSA risk factors. OSA shares genetic underpinnings with several sleep phenotypes, suggesting shared aetiology and causal pathways.

FUNDING

Described in acknowledgements.

Molecular Pathology, Oxidative Stress, and Biomarkers in Obstructive Sleep Apnea

Obstructive sleep apnea syndrome (OSAS) is characterized by intermittent hypoxia (IH) during sleep due to recurrent upper airway obstruction. The derived oxidative stress (OS) leads to complications that do not only concern the sleep-wake rhythm but also systemic dysfunctions. The aim of this narrative literature review is to investigate molecular alterations, diagnostic markers, and potential medical therapies for OSAS. We analyzed the literature and synthesized the evidence collected. IH increases oxygen free radicals (ROS) and reduces antioxidant capacities. OS and metabolic alterations lead OSAS patients to undergo endothelial dysfunction, osteoporosis, systemic inflammation, increased cardiovascular risk, pulmonary remodeling, and neurological alterations. We treated molecular alterations known to date as useful for understanding the pathogenetic mechanisms and for their potential application as diagnostic markers. The most promising pharmacological therapies are those based on N-acetylcysteine (NAC), Vitamin C, Leptin, Dronabinol, or Atomoxetine + Oxybutynin, but all require further experimentation. CPAP remains the approved therapy capable of reversing most of the known molecular alterations; future drugs may be useful in treating the remaining dysfunctions.

Discovery of genomic loci associated with sleep apnea risk through multi-trait GWAS analysis with snoring

STUDY OBJECTIVES

Despite its association with severe health conditions, the etiology of sleep apnea (SA) remains understudied. This study sought to identify genetic variants robustly associated with SA risk.

METHODS

We performed a genome-wide association study (GWAS) meta-analysis of SA across five cohorts (NTotal = 523 366), followed by a multi-trait analysis of GWAS (multi-trait analysis of genome-wide association summary statistics [MTAG]) to boost power, leveraging the high genetic correlation between SA and snoring. We then adjusted our results for the genetic effects of body mass index (BMI) using multi-trait-based conditional and joint analysis (mtCOJO) and sought replication of lead hits in a large cohort of participants from 23andMe, Inc (NTotal = 1 477 352; Ncases = 175 522). We also explored genetic correlations with other complex traits and performed a phenome-wide screen for causally associated phenotypes using the latent causal variable method.

RESULTS

Our SA meta-analysis identified five independent variants with evidence of association beyond genome-wide significance. After adjustment for BMI, only one genome-wide significant variant was identified. MTAG analyses uncovered 49 significant independent loci associated with SA risk. Twenty-nine variants were replicated in the 23andMe GWAS adjusting for BMI. We observed genetic correlations with several complex traits, including multisite chronic pain, diabetes, eye disorders, high blood pressure, osteoarthritis, chronic obstructive pulmonary disease, and BMI-associated conditions.

CONCLUSION

Our study uncovered multiple genetic loci associated with SA risk, thus increasing our understanding of the etiology of this condition and its relationship with other complex traits.

Genetics of circadian rhythms and sleep in human health and disease

Circadian rhythms and sleep are fundamental biological processes integral to human health. Their disruption is associated with detrimental physiological consequences, including cognitive, metabolic, cardiovascular and immunological dysfunctions. Yet many of the molecular underpinnings of sleep regulation in health and disease have remained elusive. Given the moderate heritability of circadian and sleep traits, genetics offers an opportunity that complements insights from model organism studies to advance our fundamental molecular understanding of human circadian and sleep physiology and linked chronic disease biology. Here, we review recent discoveries of the genetics of circadian and sleep physiology and disorders with a focus on those that reveal causal contributions to complex diseases.

Racial and ethnic differences in sleep-disordered breathing and sleep duration among stroke patients

OBJECTIVE

We sought to characterize racial and ethnic differences in pre- and post-stroke sleep-disordered breathing (SDB) and pre-stroke sleep duration.

METHODS

Within the Brain Attack Surveillance in Corpus Christi cohort of patients with ischemic stroke (8/26/2010-1/31/2020), pre-stroke SDB risk was assessed retrospectively using the Berlin Questionnaire. Post-stroke SDB was defined by prospective collection of the respiratory event index (REI) using the ApneaLink Plus performed shortly after stroke. Pre-stroke sleep duration was self-reported. We used separate regression models to evaluate the association between race/ethnicity and each outcome (pre-stroke SDB, post-stroke SDB, and pre-stroke sleep duration), without and with adjustment for potential confounders.

RESULTS

There was no difference in pre-stroke risk of SDB between Black and non-Hispanic white (NHW) participants (odds ratio (OR) 1.07, 95% CI 0.77-1.49), whereas MA (Mexican American), compared to NHW, participants had a higher risk of SDB before adjusting for demographic and clinical variables (OR 1.26, 95% CI 1.08-1.47). Post-stroke SDB risk was higher in MA (estimate 1.16, 95% CI 1.06-1.28) but lower in Black (estimate 0.79, 95% CI 0.65-0.96) compared to NHW participants; although, only the ethnic difference remained after adjustment. MA and Black participants had shorter sleep duration than NHW participants (OR 0.83, 95% CI 0.72-0.96 for MA; OR 0.67, 95% CI 0.49-0.91 for Black participants) before but not after adjustment.

CONCLUSIONS

Racial/ethnic differences appear likely to exist in pre- and post-stroke SDB and pre-stroke sleep duration. Such differences might contribute to racial/ethnic disparities in stroke incidence and outcomes.

Leveraging pleiotropy to discover and interpret GWAS results for sleep-associated traits

Genetic association studies of many heritable traits resulting from physiological testing often have modest sample sizes due to the cost and burden of the required phenotyping. This reduces statistical power and limits discovery of multiple genetic associations. We present a strategy to leverage pleiotropy between traits to both discover new loci and to provide mechanistic hypotheses of the underlying pathophysiology. Specifically, we combine a colocalization test with a locus-level test of pleiotropy. In simulations, we show that this approach is highly selective for identifying true pleiotropy driven by the same causative variant, thereby improves the chance to replicate the associations in underpowered validation cohorts and leads to higher interpretability. Here, as an exemplar, we use Obstructive Sleep Apnea (OSA), a common disorder diagnosed using overnight multi-channel physiological testing. We leverage pleiotropy with relevant cellular and cardio-metabolic phenotypes and gene expression traits to map new risk loci in an underpowered OSA GWAS. We identify several pleiotropic loci harboring suggestive associations to OSA and genome-wide significant associations to other traits, and show that their OSA association replicates in independent cohorts of diverse ancestries. By investigating pleiotropic loci, our strategy allows proposing new hypotheses about OSA pathobiology across many physiological layers. For example, we identify and replicate the pleiotropy across the plateletcrit, OSA and an eQTL of DNA primase subunit 1 (PRIM1) in immune cells. We find suggestive links between OSA, a measure of lung function (FEV1/FVC), and an eQTL of matrix metallopeptidase 15 (MMP15) in lung tissue. We also link a previously known genome-wide significant peak for OSA in the hexokinase 1 (HK1) locus to hematocrit and other red blood cell related traits. Thus, the analysis of pleiotropic associations has the potential to assemble diverse phenotypes into a chain of mechanistic hypotheses that provide insight into the pathogenesis of complex human diseases.

Advances in Molecular Pathology of Obstructive Sleep Apnea

Obstructive sleep apnea (OSA) is a common syndrome that features a complex etiology and set of mechanisms. Here we summarized the molecular pathogenesis of OSA, especially the prospective mechanism of upper? airway dilator fatigue and the current breakthroughs. Additionally, we also introduced the molecular mechanism of OSA in terms of related studies on the main signaling pathways and epigenetics alterations, such as microRNA, long non-coding RNA, and DNA methylation. We also reviewed small molecular compounds, which are potential targets for gene regulations in the future, that are involved in the regulation of OSA. This review will be beneficial to point the way for OSA research within the next decade.

Brody J, Chen H, Gottlieb DJ, Evans DS, Guo X, Gharib SA, Hale L, Hillman DR, Lutsey PL, Mukherjee S, Ochs-Balcom HM, Palmer LJ, Purcell S, Saxena R, Patel SR, Stone KL, Tranah GJ, Boerwinkle E, Lin X, Liu Y, Psaty BM, Vasan RS, Manichaikul A, Rich SS, Rotter JI, Sofer T, Redline S, Zhu X. Targeted Genome Sequencing Identifies Multiple Rare Variants in Caveolin-1 Associated with Obstructive Sleep Apnea

Rationale: Obstructive sleep apnea (OSA) is a common disorder associated with increased risk for cardiovascular disease, diabetes, and premature mortality. There is strong clinical and epidemiologic evidence supporting the importance of genetic factors influencing OSA but limited data implicating specific genes. Objectives: To search for rare variants contributing to OSA severity. Methods: Leveraging high-depth genomic sequencing data from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and imputed genotype data from multiple population-based studies, we performed linkage analysis in the CFS (Cleveland Family Study), followed by multistage gene-based association analyses in independent cohorts for apnea-hypopnea index (AHI) in a total of 7,708 individuals of European ancestry. Measurements and Main Results: Linkage analysis in the CFS identified a suggestive linkage peak on chromosome 7q31 (LOD = 2.31). Gene-based analysis identified 21 noncoding rare variants in CAV1 (Caveolin-1) associated with lower AHI after accounting for multiple comparisons (P = 7.4 × 10-8). These noncoding variants together significantly contributed to the linkage evidence (P < 10-3). Follow-up analysis revealed significant associations between these variants and increased CAV1 expression, and increased CAV1 expression in peripheral monocytes was associated with lower AHI (P = 0.024) and higher minimum overnight oxygen saturation (P = 0.007). Conclusions: Rare variants in CAV1, a membrane-scaffolding protein essential in multiple cellular and metabolic functions, are associated with higher CAV1 gene expression and lower OSA severity, suggesting a novel target for modulating OSA severity.

Genetic determinants of cardiometabolic and pulmonary phenotypes and obstructive sleep apnoea in HCHS/SOL

BACKGROUND

Obstructive Sleep Apnoea (OSA) often co-occurs with cardiometabolic and pulmonary diseases. This study is to apply genetic analysis methods to explain the associations between OSA and related phenotypes.

METHODS

In the Hispanic Community Healthy Study/Study of Latinos, we estimated genetic correlations ρ_g between the respiratory event index (REI) and 54 anthropometric, glycemic, cardiometabolic, and pulmonary phenotypes. We used summary statistics from published genome-wide association studies to construct Polygenic Risk Scores (PRSs) representing the genetic basis of each correlated phenotype (ρ_g>0.2 and p-value<0.05), and of OSA. We studied the association of the PRSs of the correlated phenotypes with both REI and OSA (REI≥5), and the association of OSA PRS with the correlated phenotypes. Causal relationships were tested using Mendelian Randomization (MR) analysis.

FINDINGS

The dataset included 11,155 participants, 31.03% with OSA. 22 phenotypes were genetically correlated with REI. 10 PRSs covering obesity and fat distribution (BMI, WHR, WHRadjBMI), blood pressure (DBP, PP, MAP), glycaemic control (fasting insulin, HbA1c, HOMA-B) and insomnia were associated with REI and/or OSA. OSA PRS was associated with BMI, WHR, DBP and glycaemic traits (fasting insulin, HbA1c, HOMA-B and HOMA-IR). MR analysis identified robust causal effects of BMI and WHR on OSA, and probable causal effects of DBP, PP, and HbA1c on OSA/REI.

INTERPRETATION

There are shared genetic underpinnings of anthropometric, blood pressure, and glycaemic phenotypes with OSA, with evidence for causal relationships between some phenotypes.

FUNDING

Described in Acknowledgments.

Heart Disease and Stroke Statistics-2022 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Upregulated heme biosynthesis increases obstructive sleep apnea severity: a pathway-based Mendelian randomization study

Obstructive sleep apnea (OSA) is a common disorder associated with increased risk of cardiovascular disease and mortality. Iron and heme metabolism, implicated in ventilatory control and OSA comorbidities, was associated with OSA phenotypes in recent admixture mapping and gene enrichment analyses. However, its causal contribution was unclear. In this study, we performed pathway-level transcriptional Mendelian randomization (MR) analysis to investigate the causal relationships between iron and heme related pathways and OSA. In primary analysis, we examined the expression level of four iron/heme Reactome pathways as exposures and four OSA traits as outcomes using cross-tissue cis-eQTLs from the Genotype-Tissue Expression portal and published genome-wide summary statistics of OSA. We identify a significant putative causal association between up-regulated heme biosynthesis pathway with higher sleep time percentage of hypoxemia (p = 6.14 × 10-3). This association is supported by consistency of point estimates in one-sample MR in the Multi-Ethnic Study of Atherosclerosis using high coverage DNA and RNA sequencing data generated by the Trans-Omics for Precision Medicine project. Secondary analysis for 37 additional iron/heme Gene Ontology pathways did not reveal any significant causal associations. This study suggests a causal association between increased heme biosynthesis and OSA severity.

Sleep apnea phenotyping and relationship to disease in a large clinical biobank

Objective

Sleep apnea is associated with a broad range of pathophysiology. While electronic health record (EHR) information has the potential for revealing relationships between sleep apnea and associated risk factors and outcomes, practical challenges hinder its use. Our objectives were to develop a sleep apnea phenotyping algorithm that improves the precision of EHR case/control information using natural language processing (NLP); identify novel associations between sleep apnea and comorbidities in a large clinical biobank; and investigate the relationship between polysomnography statistics and comorbid disease using NLP phenotyping.

Materials and Methods

We performed clinical chart reviews on 300 participants putatively diagnosed with sleep apnea and applied International Classification of Sleep Disorders criteria to classify true cases and noncases. We evaluated 2 NLP and diagnosis code-only methods for their abilities to maximize phenotyping precision. The lead algorithm was used to identify incident and cross-sectional associations between sleep apnea and common comorbidities using 4876 NLP-defined sleep apnea cases and 3× matched controls.

Results

The optimal NLP phenotyping strategy had improved model precision (≥0.943) compared to the use of one diagnosis code (≤0.733). Of the tested diseases, 170 disorders had significant incidence odds ratios (ORs) between cases and controls, 8 of which were confirmed using polysomnography (n = 4544), and 281 disorders had significant prevalence OR between sleep apnea cases versus controls, 41 of which were confirmed using polysomnography data.

Discussion and Conclusion

An NLP-informed algorithm can improve the accuracy of case-control sleep apnea ascertainment and thus improve the performance of phenome-wide, genetic, and other EHR analyses of a highly prevalent disorder.

Sleep apnea is a common disease in which breathing partially or completely pauses during sleep, leading to less oxygen in the blood, repeated awakenings, and increased risk of developing multiple diseases. Current studies of sleep apnea often have relatively few participants due to the challenge of performing overnight sleep recordings. Electronic health record (EHR) billing code diagnoses of sleep apnea could be repurposed to increase the size of research studies, but the accuracy of the diagnoses is reduced. We developed a reusable algorithm that improves the accuracy of EHR sleep apnea diagnoses using natural language processing to extract information from clinical notes. As a proof of concept, we used the algorithm to identify hundreds of diseases that are increased among participants with sleep apnea compared to similar patients without sleep apnea. Many of these disease relationships with sleep apnea have not been previously recognized. This improved algorithm will help to accelerate future large-scale investigations of the causes and consequences of sleep apnea.

An Overview of Strategies for Detecting Genotype-Phenotype Associations Across Ancestrally Diverse Populations

Genome-wide association studies (GWAS) have been very successful at identifying genetic variants influencing a large number of traits. Although the great majority of these studies have been performed in European-descent individuals, it has been recognised that including populations with differing ancestries enhances the potential for identifying causal SNPs due to their differing patterns of linkage disequilibrium. However, when individuals from distinct ethnicities are included in a GWAS, it is necessary to implement a number of control steps to ensure that the identified associations are real genotype-phenotype relationships. In this Review, we discuss the analyses that are required when performing multi-ethnic studies, including methods for determining ancestry at the global and local level for sample exclusion, controlling for ancestry in association testing, and post-GWAS interrogation methods such as genomic control and meta-analysis. We hope that this overview provides a primer for those researchers interested in including distinct populations in their studies.

Whole-genome association analyses of sleep-disordered breathing phenotypes in the NHLBI TOPMed program

BACKGROUND

Sleep-disordered breathing is a common disorder associated with significant morbidity. The genetic architecture of sleep-disordered breathing remains poorly understood. Through the NHLBI Trans-Omics for Precision Medicine (TOPMed) program, we performed the first whole-genome sequence analysis of sleep-disordered breathing.

METHODS

The study sample was comprised of 7988 individuals of diverse ancestry. Common-variant and pathway analyses included an additional 13,257 individuals. We examined five complementary traits describing different aspects of sleep-disordered breathing: the apnea-hypopnea index, average oxyhemoglobin desaturation per event, average and minimum oxyhemoglobin saturation across the sleep episode, and the percentage of sleep with oxyhemoglobin saturation < 90%. We adjusted for age, sex, BMI, study, and family structure using MMSKAT and EMMAX mixed linear model approaches. Additional bioinformatics analyses were performed with MetaXcan, GIGSEA, and ReMap.

RESULTS

We identified a multi-ethnic set-based rare-variant association (p = 3.48 × 10-8) on chromosome X with ARMCX3. Additional rare-variant associations include ARMCX3-AS1, MRPS33, and C16orf90. Novel common-variant loci were identified in the NRG1 and SLC45A2 regions, and previously associated loci in the IL18RAP and ATP2B4 regions were associated with novel phenotypes. Transcription factor binding site enrichment identified associations with genes implicated with respiratory and craniofacial traits. Additional analyses identified significantly associated pathways.

CONCLUSIONS

We have identified the first gene-based rare-variant associations with objectively measured sleep-disordered breathing traits. Our results increase the understanding of the genetic architecture of sleep-disordered breathing and highlight associations in genes that modulate lung development, inflammation, respiratory rhythmogenesis, and HIF1A-mediated hypoxic response.

Non-REM Apnea and Hypopnea Duration Varies across Population Groups and Physiologic Traits

Rationale: Symptoms and morbidities associated with obstructive sleep apnea (OSA) vary across individuals and are not predicted by the apnea-hypopnea index (AHI). Respiratory event duration is a heritable trait associated with mortality that may further characterize OSA.Objectives: We evaluated how hypopnea and apnea durations in non-REM (NREM) sleep vary across demographic groups and quantified their associations with physiological traits (loop gain, arousal threshold, circulatory delay, and pharyngeal collapsibility).Methods: Data were analyzed from 1,546 participants from the Multi-Ethnic Study of Atherosclerosis with an AHI ≥5. Physiological traits were derived using a validated model fit to the polysomnographic airflow signal. Multiple linear regression models were used to evaluate associations of event duration with demographic and physiological factors.Measurements and Main Results: Participants had a mean age ± SD of 68.9 ± 9.2 years, mean NREM hypopnea duration of 21.73 ± 5.60, and mean NREM apnea duration of 23.87 ± 7.44 seconds. In adjusted analyses, shorter events were associated with younger age, female sex, higher body mass index (P < 0.01, all), and Black race (P < 0.05). Longer events were associated with Asian race (P < 0.01). Shorter event durations were associated with lower circulatory delay (2.53 ± 0.13 s, P < 0.01), lower arousal threshold (1.39 ± 0.15 s, P < 0.01), reduced collapsibility (-0.71 ± 0.16 s, P < 0.01), and higher loop gain (-0.27 ± 0.11 s, P < 0.05) per SD change. Adjustment for physiological traits attenuated age, sex, and obesity associations and eliminated racial differences in event duration.Conclusions: Average event duration varies across population groups and provides information on ventilatory features and airway collapsibility not captured by the AHI.

Admixture mapping reveals the association between Native American ancestry at 3q13.11 and reduced risk of Alzheimer's disease in Caribbean Hispanics

BACKGROUND

Genetic studies have primarily been conducted in European ancestry populations, identifying dozens of loci associated with late-onset Alzheimer's disease (AD). However, much of AD's heritability remains unexplained; as the prevalence of AD varies across populations, the genetic architecture of the disease may also vary by population with the presence of novel variants or loci.

METHODS

We conducted genome-wide analyses of AD in a sample of 2565 Caribbean Hispanics to better understand the genetic contribution to AD in this population. Statistical analysis included both admixture mapping and association testing. Evidence for differential gene expression within regions of interest was collected from independent transcriptomic studies comparing AD cases and controls in samples with primarily European ancestry.

RESULTS

Our genome-wide association study of AD identified no loci reaching genome-wide significance. However, a genome-wide admixture mapping analysis that tests for association between a haplotype's ancestral origin and AD status detected a genome-wide significant association with chromosome 3q13.11 (103.7-107.7Mb, P = 8.76E-07), driven by a protective effect conferred by the Native American ancestry (OR = 0.58, 95%CI = 0.47-0.73). Within this region, two variants were significantly associated with AD after accounting for the number of independent tests (rs12494162, P = 2.33E-06; rs1731642, P = 6.36E-05). The significant admixture mapping signal is composed of 15 haplotype blocks spanning 5 protein-coding genes (ALCAM, BBX, CBLB, CCDC54, CD47) and four brain-derived topologically associated domains, and includes markers significantly associated with the expression of ALCAM, BBX, CBLB, and CD47 in the brain. ALCAM and BBX were also significantly differentially expressed in the brain between AD cases and controls with European ancestry.

CONCLUSION

These results provide multiethnic evidence for a relationship between AD and multiple genes at 3q13.11 and illustrate the utility of leveraging genetic ancestry diversity via admixture mapping for new insights into AD.

Genome-wide admixture mapping of DSM-IV alcohol dependence, criterion count, and the self-rating of the effects of ethanol in African American populations

African Americans (AA) have lower prevalence of alcohol dependence and higher subjective response to alcohol than European Americans. Genome-wide association studies (GWAS) have identified genes/variants associated with alcohol dependence specifically in AA; however, the sample sizes are still not large enough to detect variants with small effects. Admixture mapping is an alternative way to identify alcohol dependence genes/variants that may be unique to AA. In this study, we performed the first admixture mapping of DSM-IV alcohol dependence diagnosis, DSM-IV alcohol dependence criterion count, and two scores from the self-rating of effects of ethanol (SRE) as measures of response to alcohol: the first five times of using alcohol (SRE-5) and average of SRE across three times (SRE-T). Findings revealed a region on chromosome 4 that was genome-wide significant for SRE-5 (p value = 4.18E-05). Fine mapping did not identify a single causal variant to be associated with SRE-5; instead, conditional analysis concluded that multiple variants collectively explained the admixture mapping signal. PPARGC1A, a gene that has been linked to alcohol consumption in previous studies, is located in this region. Our finding suggests that admixture mapping is a useful tool to identify genes/variants that may have been missed by current GWAS approaches in admixed populations.

Heart Disease and Stroke Statistics-2021 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2021 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors related to cardiovascular disease.

RESULTS

Each of the 27 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Pediatric Obstructive Sleep Apnea and Neurocognition

Pediatric obstructive sleep apnea affects a large number of children and has multiple end-organ sequelae. Although many of these have been demonstrated to be reversible, the effects on some of the organ systems, including the brain, have not shown easy reversibility. Progress in this area has been hampered by lack of a preclinical model to study the disease. Therefore, perioperative and sleep physicians are tasked with making a number of difficult decisions, including optimal surgical timing to prevent disease evolution, but also to keep the perioperative morbidity in a safe range for these patients.

Prospective avenues for human population genomics and disease mapping in southern Africa

Population substructure within human populations is globally evident and a well-known confounding factor in many genetic studies. In contrast, admixture mapping exploits population stratification to detect genotype-phenotype correlations in admixed populations. Southern Africa has untapped potential for disease mapping of ancestry-specific disease risk alleles due to the distinct genetic diversity in its populations compared to other populations worldwide. This diversity contributes to a number of phenotypes, including ancestry-specific disease risk and response to pathogens. Although the 1000 Genomes Project significantly improved our understanding of genetic variation globally, southern African populations are still severely underrepresented in biomedical and human genetic studies due to insufficient large-scale publicly available data. In addition to a lack of genetic data in public repositories, existing software, algorithms and resources used for imputation and phasing of genotypic data (amongst others) are largely ineffective for populations with a complex genetic architecture such as that seen in southern Africa. This review article, therefore, aims to summarise the current limitations of conducting genetic studies on populations with a complex genetic architecture to identify potential areas for further research and development.

Low oxygen saturation during sleep reduces CD1D and RAB20 expressions that are reversed by CPAP therapy

BACKGROUND

Sleep Disordered Breathing (SDB) is associated with a wide range of pathophysiological changes due, in part, to hypoxemia during sleep. We sought to identify gene transcription associations with measures of SDB and hypoxemia during sleep, and study their response to treatment.

METHODS

In two discovery cohorts, Framingham Offspring Study (FOS; N = 571) and the Multi-Ethnic Study of Atherosclerosis (MESA; N = 580), we studied gene expression in peripheral blood mononuclear cells in association with three measures of SDB: Apnea Hypopnea Index (AHI); average oxyhemoglobin saturation (avgO2) during sleep; and minimum oxyhemoglobin saturation (minO2) during sleep. Associated genes were used for analysis of gene expression in the blood of 15 participants with moderate or severe obstructive sleep apnea (OSA) from the Heart Biomarkers In Apnea Treatment (HeartBEAT) trial. These genes were studied pre- and post-treatment (three months) with continuous positive airway pressure (CPAP). We also performed Gene Set Enrichment Analysis (GSEA) on all traits and cohort analyses.

FINDINGS

Twenty-two genes were associated with SDB traits in both MESA and FOS. Of these, lower expression of CD1D and RAB20 was associated with lower avgO2 in MESA and FOS. CPAP treatment increased the expression of these genes in HeartBEAT participants. Immunity and inflammation pathways were up-regulated in subjects with lower avgO2; i.e., in those with a more severe SDB phenotype (MESA), whereas immuno-inflammatory processes were down-regulated following CPAP treatment (HeartBEAT).

INTERPRETATION

Low oxygen saturation during sleep is associated with alterations in gene expression and transcriptional programs that are partially reversed by CPAP treatment.

Mixed-model admixture mapping identifies smoking-dependent loci of lung function in African Americans

Admixture mapping has led to the discovery of many genes associated with differential disease risk by ancestry, highlighting the importance of ancestry-based approaches to association studies. However, the potential of admixture mapping in deciphering the interplay between genes and environment exposures has been seldom explored. Here we performed a genome-wide screening of local ancestry-smoking interactions for five spirometric lung function phenotypes in 3300 African Americans from the COPDGene study. To account for population structure and outcome heterogeneity across exposure groups, we developed a multi-component linear mixed model for mapping gene-environment interactions and empirically showed its robustness and increased power. When applied to the COPDGene study, our approach identified two 11p15.2-3 and 2q37 loci, exhibiting local ancestry-smoking interactions at genome-wide significant level, which would have been missed by standard single-nucleotide polymorphism analyses. These two loci harbor the PARVA and RAB17 genes previously recognized to be involved in smoking behavior. Overall, our study provides the first evidence for potential synergistic effects between African ancestry and smoking on pulmonary function, and underlines the importance of ethnic diversity in genetic studies.

Local Ancestry Inference in Large Pedigrees

Local ancestry, defined as the genetic ancestry at a genomic location of an admixed individual, is widely used as a genetic marker in genetic association and evolutionary genetics studies. Many methods have been developed to infer the local ancestries in a set of unrelated individuals, a few of them have been extended to small nuclear families, but none can be applied to large (e.g. three-generation) pedigrees. In this study, we developed a method, FamANC, that can improve the accuracy of local ancestry inference in large pedigrees by: (1) using an existing algorithm to infer local ancestries for all individuals in a family, assuming (contrary to fact) they are unrelated, and (2) improving its accuracy by correcting inference errors using pedigree structure. Applied on African-American pedigrees from the Cleveland Family Study, FamANC was able to correct all identified Mendelian errors and most of double crossovers.

More Than the Sum of the Respiratory Events: Personalized Medicine Approaches for Obstructive Sleep Apnea

Traditionally, the presence and severity of obstructive sleep apnea (OSA) have been defined by the apnea-hypopnea index (AHI). Continuous positive airway pressure is generally first-line therapy despite low adherence, because it reliably reduces the AHI when used, and the response to other therapies is variable. However, there is growing appreciation that the underlying etiology (i.e., endotype) and clinical manifestation (i.e., phenotype) of OSA in an individual are not well described by the AHI. We define and review the important progress made in understanding and measuring physiological mechanisms (or endotypes) that help define subtypes of OSA and identify the potential use of genetics to further refine disease classification. This more detailed understanding of OSA pathogenesis should influence clinical treatment decisions as well as help inform research priorities and clinical study design. In short, treatments could be individualized on the basis of the underlying cause of OSA; patients could better understand which symptoms and outcomes will respond to OSA treatment and by how much; and researchers could select populations most likely to benefit from specific treatment approaches for OSA.

Genome-wide Significance Thresholds for Admixture Mapping Studies

Admixture mapping studies have become more common in recent years, due in part to technological advances and growing international efforts to increase the diversity of genetic studies. However, many open questions remain about appropriate implementation of admixture mapping studies, including how best to control for multiple testing, particularly in the presence of population structure. In this study, we develop a theoretical framework to characterize the correlation of local ancestry and admixture mapping test statistics in admixed populations with contributions from any number of ancestral populations and arbitrary population structure. Based on this framework, we develop an analytical approach for obtaining genome-wide significance thresholds for admixture mapping studies. We validate our approach via analysis of simulated traits with real genotype data for 8,064 unrelated African American and 3,425 Hispanic/Latina women from the Women's Health Initiative SNP Health Association Resource (WHI SHARe). In an application to these WHI SHARe data, our approach yields genome-wide significant p value thresholds of 2.1 × 10-5 and 4.5 × 10-6 for admixture mapping studies in the African American and Hispanic/Latina cohorts, respectively. Compared to other commonly used multiple testing correction procedures, our method is fast, easy to implement (using our publicly available R package), and controls the family-wise error rate even in structured populations. Importantly, we note that the appropriate admixture mapping significance threshold depends on the number of ancestral populations, generations since admixture, and population structure of the sample; as a result, significance thresholds are not, in general, transferable across studies.