@article {8044, title = {Associations of variants In the hexokinase 1 and interleukin 18 receptor regions with oxyhemoglobin saturation during sleep.}, journal = {PLoS Genet}, volume = {15}, year = {2019}, month = {2019 04}, pages = {e1007739}, abstract = {

Sleep disordered breathing (SDB)-related overnight hypoxemia is associated with cardiometabolic disease and other comorbidities. Understanding the genetic bases for variations in nocturnal hypoxemia may help understand mechanisms influencing oxygenation and SDB-related mortality. We conducted genome-wide association tests across 10 cohorts and 4 populations to identify genetic variants associated with three correlated measures of overnight oxyhemoglobin saturation: average and minimum oxyhemoglobin saturation during sleep and the percent of sleep with oxyhemoglobin saturation under 90\%. The discovery sample consisted of 8,326 individuals. Variants with p < 1 {\texttimes} 10(-6) were analyzed in a replication group of 14,410 individuals. We identified 3 significantly associated regions, including 2 regions in multi-ethnic analyses (2q12, 10q22). SNPs in the 2q12 region associated with minimum SpO2 (rs78136548 p = 2.70 {\texttimes} 10(-10)). SNPs at 10q22 were associated with all three traits including average SpO2 (rs72805692 p = 4.58 {\texttimes} 10(-8)). SNPs in both regions were associated in over 20,000 individuals and are supported by prior associations or functional evidence. Four additional significant regions were detected in secondary sex-stratified and combined discovery and replication analyses, including a region overlapping Reelin, a known marker of respiratory complex neurons.These are the first genome-wide significant findings reported for oxyhemoglobin saturation during sleep, a phenotype of high clinical interest. Our replicated associations with HK1 and IL18R1 suggest that variants in inflammatory pathways, such as the biologically-plausible NLRP3 inflammasome, may contribute to nocturnal hypoxemia.

}, keywords = {Adolescent, Adult, Aged, Aged, 80 and over, Cell Adhesion Molecules, Neuronal, Computational Biology, Extracellular Matrix Proteins, Female, Gene Regulatory Networks, Genetic Variation, Genome-Wide Association Study, Hexokinase, Humans, Hypoxia, Interleukin-18 Receptor alpha Subunit, Male, Middle Aged, Nerve Tissue Proteins, NLR Family, Pyrin Domain-Containing 3 Protein, Oxygen, Oxyhemoglobins, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Serine Endopeptidases, Sleep, Sleep Apnea Syndromes, Young Adult}, issn = {1553-7404}, doi = {10.1371/journal.pgen.1007739}, author = {Cade, Brian E and Chen, Han and Stilp, Adrienne M and Louie, Tin and Ancoli-Israel, Sonia and Arens, Raanan and Barfield, Richard and Below, Jennifer E and Cai, Jianwen and Conomos, Matthew P and Evans, Daniel S and Frazier-Wood, Alexis C and Gharib, Sina A and Gleason, Kevin J and Gottlieb, Daniel J and Hillman, David R and Johnson, W Craig and Lederer, David J and Lee, Jiwon and Loredo, Jose S and Mei, Hao and Mukherjee, Sutapa and Patel, Sanjay R and Post, Wendy S and Purcell, Shaun M and Ramos, Alberto R and Reid, Kathryn J and Rice, Ken and Shah, Neomi A and Sofer, Tamar and Taylor, Kent D and Thornton, Timothy A and Wang, Heming and Yaffe, Kristine and Zee, Phyllis C and Hanis, Craig L and Palmer, Lyle J and Rotter, Jerome I and Stone, Katie L and Tranah, Gregory J and Wilson, James G and Sunyaev, Shamil R and Laurie, Cathy C and Zhu, Xiaofeng and Saxena, Richa and Lin, Xihong and Redline, Susan} } @article {8202, title = {Multi-ancestry sleep-by-SNP interaction analysis in 126,926 individuals reveals lipid loci stratified by sleep duration.}, journal = {Nat Commun}, volume = {10}, year = {2019}, month = {2019 Nov 12}, pages = {5121}, abstract = {

Both short and long sleep are associated with an adverse lipid profile, likely through different biological pathways. To elucidate the biology of sleep-associated adverse lipid profile, we conduct multi-ancestry genome-wide sleep-SNP interaction analyses on three lipid traits (HDL-c, LDL-c and triglycerides). In the total study sample (discovery + replication) of 126,926 individuals from 5 different ancestry groups, when considering either long or short total sleep time interactions in joint analyses, we identify 49 previously unreported lipid loci, and 10 additional previously unreported lipid loci in a restricted sample of European-ancestry cohorts. In addition, we identify new gene-sleep interactions for known lipid loci such as LPL and PCSK9. The previously unreported lipid loci have a modest explained variance in lipid levels: most notable, gene-short-sleep interactions explain 4.25\% of the variance in triglyceride level. Collectively, these findings contribute to our understanding of the biological mechanisms involved in sleep-associated adverse lipid profiles.

}, issn = {2041-1723}, doi = {10.1038/s41467-019-12958-0}, author = {Noordam, Raymond and Bos, Maxime M and Wang, Heming and Winkler, Thomas W and Bentley, Amy R and Kilpel{\"a}inen, Tuomas O and de Vries, Paul S and Sung, Yun Ju and Schwander, Karen and Cade, Brian E and Manning, Alisa and Aschard, Hugues and Brown, Michael R and Chen, Han and Franceschini, Nora and Musani, Solomon K and Richard, Melissa and Vojinovic, Dina and Aslibekyan, Stella and Bartz, Traci M and de Las Fuentes, Lisa and Feitosa, Mary and Horimoto, Andrea R and Ilkov, Marjan and Kho, Minjung and Kraja, Aldi and Li, Changwei and Lim, Elise and Liu, Yongmei and Mook-Kanamori, Dennis O and Rankinen, Tuomo and Tajuddin, Salman M and van der Spek, Ashley and Wang, Zhe and Marten, Jonathan and Laville, Vincent and Alver, Maris and Evangelou, Evangelos and Graff, Maria E and He, Meian and Kuhnel, Brigitte and Lyytik{\"a}inen, Leo-Pekka and Marques-Vidal, Pedro and Nolte, Ilja M and Palmer, Nicholette D and Rauramaa, Rainer and Shu, Xiao-Ou and Snieder, Harold and Weiss, Stefan and Wen, Wanqing and Yanek, Lisa R and Adolfo, Correa and Ballantyne, Christie and Bielak, Larry and Biermasz, Nienke R and Boerwinkle, Eric and Dimou, Niki and Eiriksdottir, Gudny and Gao, Chuan and Gharib, Sina A and Gottlieb, Daniel J and Haba-Rubio, Jos{\'e} and Harris, Tamara B and Heikkinen, Sami and Heinzer, Raphael and Hixson, James E and Homuth, Georg and Ikram, M Arfan and Komulainen, Pirjo and Krieger, Jose E and Lee, Jiwon and Liu, Jingmin and Lohman, Kurt K and Luik, Annemarie I and M{\"a}gi, Reedik and Martin, Lisa W and Meitinger, Thomas and Metspalu, Andres and Milaneschi, Yuri and Nalls, Mike A and O{\textquoteright}Connell, Jeff and Peters, Annette and Peyser, Patricia and Raitakari, Olli T and Reiner, Alex P and Rensen, Patrick C N and Rice, Treva K and Rich, Stephen S and Roenneberg, Till and Rotter, Jerome I and Schreiner, Pamela J and Shikany, James and Sidney, Stephen S and Sims, Mario and Sitlani, Colleen M and Sofer, Tamar and Strauch, Konstantin and Swertz, Morris A and Taylor, Kent D and Uitterlinden, Andr{\'e} G and van Duijn, Cornelia M and V{\"o}lzke, Henry and Waldenberger, Melanie and Wallance, Robert B and van Dijk, Ko Willems and Yu, Caizheng and Zonderman, Alan B and Becker, Diane M and Elliott, Paul and Esko, T{\~o}nu and Gieger, Christian and Grabe, Hans J and Lakka, Timo A and Lehtim{\"a}ki, Terho and North, Kari E and Penninx, Brenda W J H and Vollenweider, Peter and Wagenknecht, Lynne E and Wu, Tangchun and Xiang, Yong-Bing and Zheng, Wei and Arnett, Donna K and Bouchard, Claude and Evans, Michele K and Gudnason, Vilmundur and Kardia, Sharon and Kelly, Tanika N and Kritchevsky, Stephen B and Loos, Ruth J F and Pereira, Alexandre C and Province, Mike and Psaty, Bruce M and Rotimi, Charles and Zhu, Xiaofeng and Amin, Najaf and Cupples, L Adrienne and Fornage, Myriam and Fox, Ervin F and Guo, Xiuqing and Gauderman, W James and Rice, Kenneth and Kooperberg, Charles and Munroe, Patricia B and Liu, Ching-Ti and Morrison, Alanna C and Rao, Dabeeru C and van Heemst, Diana and Redline, Susan} } @article {8199, title = {Sequencing Analysis at 8p23 Identifies Multiple Rare Variants in DLC1 Associated with Sleep-Related Oxyhemoglobin Saturation Level.}, journal = {Am J Hum Genet}, volume = {105}, year = {2019}, month = {2019 Nov 07}, pages = {1057-1068}, abstract = {

Average arterial oxyhemoglobin saturation during sleep (AvSpOS) is a clinically relevant measure of physiological stress associated with sleep-disordered breathing, and this measure predicts incident cardiovascular disease and mortality. Using high-depth whole-genome sequencing data from the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) project and focusing on genes with linkage evidence on chromosome 8p23, we observed that six coding and 51 noncoding variants in a gene that encodes the GTPase-activating protein (DLC1) are significantly associated with AvSpOS and replicated in independent subjects. The combined DLC1 association evidence of discovery and replication cohorts reaches genome-wide significance in European Americans (p = 7.9~{\texttimes} 10). A risk score for these variants, built on an independent dataset, explains 0.97\% of the AvSpOS variation and contributes to the linkage evidence. The 51 noncoding variants are enriched in regulatory features in a human lung fibroblast cell line and contribute to DLC1 expression variation. Mendelian randomization analysis using these variants indicates a significant causal effect of DLC1 expression in fibroblasts on AvSpOS. Multiple sources of information, including genetic variants, gene expression, and methylation, consistently suggest that DLC1 is a gene associated with AvSpOS.

}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2019.10.002}, author = {Liang, Jingjing and Cade, Brian E and He, Karen Y and Wang, Heming and Lee, Jiwon and Sofer, Tamar and Williams, Stephanie and Li, Ruitong and Chen, Han and Gottlieb, Daniel J and Evans, Daniel S and Guo, Xiuqing and Gharib, Sina A and Hale, Lauren and Hillman, David R and Lutsey, Pamela L and Mukherjee, Sutapa and Ochs-Balcom, Heather M and Palmer, Lyle J and Rhodes, Jessica and Purcell, Shaun and Patel, Sanjay R and Saxena, Richa and Stone, Katie L and Tang, Weihong and Tranah, Gregory J and Boerwinkle, Eric and Lin, Xihong and Liu, Yongmei and Psaty, Bruce M and Vasan, Ramachandran S and Cho, Michael H and Manichaikul, Ani and Silverman, Edwin K and Barr, R Graham and Rich, Stephen S and Rotter, Jerome I and Wilson, James G and Redline, Susan and Zhu, Xiaofeng} } @article {8621, title = {Inherited causes of clonal haematopoiesis in 97,691 whole genomes.}, journal = {Nature}, volume = {586}, year = {2020}, month = {2020 10}, pages = {763-768}, abstract = {

Age is the dominant risk factor for most chronic human diseases, but the mechanisms through which ageing confers this risk are largely unknown. The age-related acquisition of somatic mutations that lead to clonal expansion in regenerating haematopoietic stem cell populations has recently been associated with both haematological cancer and coronary heart disease-this phenomenon is~termed clonal haematopoiesis of indeterminate potential (CHIP). Simultaneous analyses of germline and somatic whole-genome sequences provide the opportunity to identify root causes of CHIP. Here we analyse high-coverage whole-genome sequences from 97,691 participants of diverse ancestries in the National Heart, Lung, and Blood Institute Trans-omics for Precision Medicine (TOPMed) programme, and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid and inflammatory traits that are specific to different CHIP~driver genes. Association of a genome-wide set of germline genetic variants enabled the identification of three genetic loci associated with CHIP status, including one locus at TET2 that was specific to individuals of African ancestry. In silico-informed in vitro evaluation of the TET2 germline locus enabled the identification of a causal variant that disrupts a TET2 distal enhancer, resulting in increased self-renewal of haematopoietic stem cells. Overall, we observe that germline genetic variation shapes haematopoietic stem cell function, leading to CHIP through mechanisms that are specific to clonal haematopoiesis as well as shared mechanisms that lead to somatic mutations across tissues.

}, issn = {1476-4687}, doi = {10.1038/s41586-020-2819-2}, author = {Bick, Alexander G and Weinstock, Joshua S and Nandakumar, Satish K and Fulco, Charles P and Bao, Erik L and Zekavat, Seyedeh M and Szeto, Mindy D and Liao, Xiaotian and Leventhal, Matthew J and Nasser, Joseph and Chang, Kyle and Laurie, Cecelia and Burugula, Bala Bharathi and Gibson, Christopher J and Lin, Amy E and Taub, Margaret A and Aguet, Francois and Ardlie, Kristin and Mitchell, Braxton D and Barnes, Kathleen C and Moscati, Arden and Fornage, Myriam and Redline, Susan and Psaty, Bruce M and Silverman, Edwin K and Weiss, Scott T and Palmer, Nicholette D and Vasan, Ramachandran S and Burchard, Esteban G and Kardia, Sharon L R and He, Jiang and Kaplan, Robert C and Smith, Nicholas L and Arnett, Donna K and Schwartz, David A and Correa, Adolfo and de Andrade, Mariza and Guo, Xiuqing and Konkle, Barbara A and Custer, Brian and Peralta, Juan M and Gui, Hongsheng and Meyers, Deborah A and McGarvey, Stephen T and Chen, Ida Yii-Der and Shoemaker, M Benjamin and Peyser, Patricia A and Broome, Jai G and Gogarten, Stephanie M and Wang, Fei Fei and Wong, Quenna and Montasser, May E and Daya, Michelle and Kenny, Eimear E and North, Kari E and Launer, Lenore J and Cade, Brian E and Bis, Joshua C and Cho, Michael H and Lasky-Su, Jessica and Bowden, Donald W and Cupples, L Adrienne and Mak, Angel C Y and Becker, Lewis C and Smith, Jennifer A and Kelly, Tanika N and Aslibekyan, Stella and Heckbert, Susan R and Tiwari, Hemant K and Yang, Ivana V and Heit, John A and Lubitz, Steven A and Johnsen, Jill M and Curran, Joanne E and Wenzel, Sally E and Weeks, Daniel E and Rao, Dabeeru C and Darbar, Dawood and Moon, Jee-Young and Tracy, Russell P and Buth, Erin J and Rafaels, Nicholas and Loos, Ruth J F and Durda, Peter and Liu, Yongmei and Hou, Lifang and Lee, Jiwon and Kachroo, Priyadarshini and Freedman, Barry I and Levy, Daniel and Bielak, Lawrence F and Hixson, James E and Floyd, James S and Whitsel, Eric A and Ellinor, Patrick T and Irvin, Marguerite R and Fingerlin, Tasha E and Raffield, Laura M and Armasu, Sebastian M and Wheeler, Marsha M and Sabino, Ester C and Blangero, John and Williams, L Keoki and Levy, Bruce D and Sheu, Wayne Huey-Herng and Roden, Dan M and Boerwinkle, Eric and Manson, JoAnn E and Mathias, Rasika A and Desai, Pinkal and Taylor, Kent D and Johnson, Andrew D and Auer, Paul L and Kooperberg, Charles and Laurie, Cathy C and Blackwell, Thomas W and Smith, Albert V and Zhao, Hongyu and Lange, Ethan and Lange, Leslie and Rich, Stephen S and Rotter, Jerome I and Wilson, James G and Scheet, Paul and Kitzman, Jacob O and Lander, Eric S and Engreitz, Jesse M and Ebert, Benjamin L and Reiner, Alexander P and Jaiswal, Siddhartha and Abecasis, Goncalo and Sankaran, Vijay G and Kathiresan, Sekar and Natarajan, Pradeep} } @article {8407, title = {Role of Rare and Low-Frequency Variants in Gene-Alcohol Interactions on Plasma Lipid Levels.}, journal = {Circ Genom Precis Med}, volume = {13}, year = {2020}, month = {2020 Aug}, pages = {e002772}, abstract = {

BACKGROUND: Alcohol intake influences plasma lipid levels, and such effects may be moderated by genetic variants. We aimed to characterize the role of aggregated rare and low-frequency protein-coding variants in gene by alcohol consumption interactions associated with fasting plasma lipid levels.

METHODS: In the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium, fasting plasma triglycerides and high- and low-density lipoprotein cholesterol were measured in 34 153 individuals with European ancestry from 5 discovery studies and 32 277 individuals from 6 replication studies. Rare and low-frequency functional protein-coding variants (minor allele frequency, <=5\%) measured by an exome array were aggregated by genes and evaluated by a gene-environment interaction test and a joint test of genetic main and gene-environment interaction effects. Two dichotomous self-reported alcohol consumption variables, current drinker, defined as any recurrent drinking behavior, and regular drinker, defined as the subset of current drinkers who consume at least 2 drinks per week, were considered.

RESULTS: We discovered and replicated 21 gene-lipid associations at 13 known lipid loci through the joint test. Eight loci (, , , , , , , and ) remained significant after conditioning on the common index single-nucleotide polymorphism identified by previous genome-wide association studies, suggesting an independent role for rare and low-frequency variants at these loci. One significant gene-alcohol interaction on triglycerides in a novel locus was significantly discovered (=6.65{\texttimes}10 for the interaction test) and replicated at nominal significance level (=0.013) in .

CONCLUSIONS: In conclusion, this study applied new gene-based statistical approaches and suggested that rare and low-frequency genetic variants interacted with alcohol consumption on lipid levels.

}, issn = {2574-8300}, doi = {10.1161/CIRCGEN.119.002772}, author = {Wang, Zhe and Chen, Han and Bartz, Traci M and Bielak, Lawrence F and Chasman, Daniel I and Feitosa, Mary F and Franceschini, Nora and Guo, Xiuqing and Lim, Elise and Noordam, Raymond and Richard, Melissa A and Wang, Heming and Cade, Brian and Cupples, L Adrienne and de Vries, Paul S and Giulanini, Franco and Lee, Jiwon and Lemaitre, Rozenn N and Martin, Lisa W and Reiner, Alex P and Rich, Stephen S and Schreiner, Pamela J and Sidney, Stephen and Sitlani, Colleen M and Smith, Jennifer A and Willems van Dijk, Ko and Yao, Jie and Zhao, Wei and Fornage, Myriam and Kardia, Sharon L R and Kooperberg, Charles and Liu, Ching-Ti and Mook-Kanamori, Dennis O and Province, Michael A and Psaty, Bruce M and Redline, Susan and Ridker, Paul M and Rotter, Jerome I and Boerwinkle, Eric and Morrison, Alanna C} } @article {8639, title = {Whole genome sequence analysis of pulmonary function and COPD in 19,996 multi-ethnic participants.}, journal = {Nat Commun}, volume = {11}, year = {2020}, month = {2020 10 14}, pages = {5182}, abstract = {

Chronic obstructive pulmonary disease (COPD), diagnosed by reduced lung function, is a leading cause of morbidity and mortality. We performed whole genome sequence (WGS) analysis of lung function and COPD in a multi-ethnic sample of 11,497 participants from population- and family-based studies, and 8499 individuals from COPD-enriched studies in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program. We identify at genome-wide significance 10 known GWAS loci and 22 distinct, previously unreported loci, including two common variant signals from stratified analysis of African Americans. Four novel common variants within the regions of PIAS1, RGN (two variants) and FTO show evidence of replication in the UK Biobank (European ancestry n ~ 320,000), while colocalization analyses leveraging multi-omic data from GTEx and TOPMed identify potential molecular mechanisms underlying four of the 22 novel loci. Our study demonstrates the value of performing WGS analyses and multi-omic follow-up in cohorts of diverse ancestry.

}, keywords = {Adult, African Americans, Aged, Aged, 80 and over, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Calcium-Binding Proteins, Feasibility Studies, Female, Follow-Up Studies, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Intracellular Signaling Peptides and Proteins, Lung, Male, Middle Aged, Polymorphism, Single Nucleotide, Protein Inhibitors of Activated STAT, Pulmonary Disease, Chronic Obstructive, Respiratory Physiological Phenomena, Small Ubiquitin-Related Modifier Proteins, Whole Genome Sequencing}, issn = {2041-1723}, doi = {10.1038/s41467-020-18334-7}, author = {Zhao, Xutong and Qiao, Dandi and Yang, Chaojie and Kasela, Silva and Kim, Wonji and Ma, Yanlin and Shrine, Nick and Batini, Chiara and Sofer, Tamar and Taliun, Sarah A Gagliano and Sakornsakolpat, Phuwanat and Balte, Pallavi P and Prokopenko, Dmitry and Yu, Bing and Lange, Leslie A and Dupuis, Jos{\'e}e and Cade, Brian E and Lee, Jiwon and Gharib, Sina A and Daya, Michelle and Laurie, Cecelia A and Ruczinski, Ingo and Cupples, L Adrienne and Loehr, Laura R and Bartz, Traci M and Morrison, Alanna C and Psaty, Bruce M and Vasan, Ramachandran S and Wilson, James G and Taylor, Kent D and Durda, Peter and Johnson, W Craig and Cornell, Elaine and Guo, Xiuqing and Liu, Yongmei and Tracy, Russell P and Ardlie, Kristin G and Aguet, Francois and VanDenBerg, David J and Papanicolaou, George J and Rotter, Jerome I and Barnes, Kathleen C and Jain, Deepti and Nickerson, Deborah A and Muzny, Donna M and Metcalf, Ginger A and Doddapaneni, Harshavardhan and Dugan-Perez, Shannon and Gupta, Namrata and Gabriel, Stacey and Rich, Stephen S and O{\textquoteright}Connor, George T and Redline, Susan and Reed, Robert M and Laurie, Cathy C and Daviglus, Martha L and Preudhomme, Liana K and Burkart, Kristin M and Kaplan, Robert C and Wain, Louise V and Tobin, Martin D and London, Stephanie J and Lappalainen, Tuuli and Oelsner, Elizabeth C and Abecasis, Goncalo R and Silverman, Edwin K and Barr, R Graham and Cho, Michael H and Manichaikul, Ani} } @article {8838, title = {BinomiRare: A robust test for association of a rare genetic variant with a binary outcome for mixed models and any case-control proportion.}, journal = {HGG Adv}, volume = {2}, year = {2021}, month = {2021 Jul 08}, abstract = {

Whole-genome sequencing (WGS) and whole-exome sequencing studies have become increasingly available and are being used to identify rare genetic variants associated with health and disease outcomes. Investigators routinely use mixed models to account for genetic relatedness or other clustering variables (e.g., family or household) when testing genetic associations. However, no existing tests of the association of a rare variant with a binary outcome in the presence of correlated data control the type 1 error where there are (1) few individuals harboring the rare allele, (2) a small proportion of cases relative to controls, and (3) covariates to adjust for. Here, we address all three issues in developing a framework for testing rare variant association with a binary trait in individuals harboring at least one risk allele. In this framework, we estimate outcome probabilities under the null hypothesis and then use them, within the individuals with at least one risk allele, to test variant associations. We extend the BinomiRare test, which was previously proposed for independent observations, and develop the Conway-Maxwell-Poisson (CMP) test and study their properties in simulations. We show that the BinomiRare test always controls the type 1 error, while the CMP test sometimes does not. We then use the BinomiRare test to test the association of rare genetic variants in target genes with small-vessel disease (SVD) stroke, short sleep, and venous thromboembolism (VTE), in whole-genome sequence data from the Trans-Omics for Precision Medicine (TOPMed) program.

}, issn = {2666-2477}, doi = {10.1016/j.xhgg.2021.100040}, author = {Sofer, Tamar and Lee, Jiwon and Kurniansyah, Nuzulul and Jain, Deepti and Laurie, Cecelia A and Gogarten, Stephanie M and Conomos, Matthew P and Heavner, Ben and Hu, Yao and Kooperberg, Charles and Haessler, Jeffrey and Vasan, Ramachandran S and Cupples, L Adrienne and Coombes, Brandon J and Seyerle, Amanda and Gharib, Sina A and Chen, Han and O{\textquoteright}Connell, Jeffrey R and Zhang, Man and Gottlieb, Daniel J and Psaty, Bruce M and Longstreth, W T and Rotter, Jerome I and Taylor, Kent D and Rich, Stephen S and Guo, Xiuqing and Boerwinkle, Eric and Morrison, Alanna C and Pankow, James S and Johnson, Andrew D and Pankratz, Nathan and Reiner, Alex P and Redline, Susan and Smith, Nicholas L and Rice, Kenneth M and Schifano, Elizabeth D} } @article {8711, title = {Chromosome Xq23 is associated with lower atherogenic lipid concentrations and favorable cardiometabolic indices.}, journal = {Nat Commun}, volume = {12}, year = {2021}, month = {2021 04 12}, pages = {2182}, abstract = {

Autosomal genetic analyses of blood lipids have yielded key insights for coronary heart disease (CHD). However, X chromosome genetic variation is understudied for blood lipids in large sample sizes. We now analyze genetic and blood lipid data in a high-coverage whole X chromosome sequencing study of 65,322 multi-ancestry participants and perform replication among 456,893 European participants. Common alleles on chromosome Xq23 are strongly associated with reduced total cholesterol, LDL cholesterol, and triglycerides (min P = 8.5 {\texttimes} 10), with similar effects for males and females. Chromosome Xq23 lipid-lowering alleles are associated with reduced odds for CHD among 42,545 cases and 591,247 controls (P = 1.7 {\texttimes} 10), and reduced odds for diabetes mellitus type 2 among 54,095 cases and 573,885 controls (P = 1.4 {\texttimes} 10). Although we observe an association with increased BMI, waist-to-hip ratio adjusted for BMI is reduced, bioimpedance analyses indicate increased gluteofemoral fat, and abdominal MRI analyses indicate reduced visceral adiposity. Co-localization analyses strongly correlate increased CHRDL1 gene expression, particularly in adipose tissue, with reduced concentrations of blood lipids.

}, issn = {2041-1723}, doi = {10.1038/s41467-021-22339-1}, author = {Natarajan, Pradeep and Pampana, Akhil and Graham, Sarah E and Ruotsalainen, Sanni E and Perry, James A and de Vries, Paul S and Broome, Jai G and Pirruccello, James P and Honigberg, Michael C and Aragam, Krishna and Wolford, Brooke and Brody, Jennifer A and Antonacci-Fulton, Lucinda and Arden, Moscati and Aslibekyan, Stella and Assimes, Themistocles L and Ballantyne, Christie M and Bielak, Lawrence F and Bis, Joshua C and Cade, Brian E and Do, Ron and Doddapaneni, Harsha and Emery, Leslie S and Hung, Yi-Jen and Irvin, Marguerite R and Khan, Alyna T and Lange, Leslie and Lee, Jiwon and Lemaitre, Rozenn N and Martin, Lisa W and Metcalf, Ginger and Montasser, May E and Moon, Jee-Young and Muzny, Donna and O{\textquoteright}Connell, Jeffrey R and Palmer, Nicholette D and Peralta, Juan M and Peyser, Patricia A and Stilp, Adrienne M and Tsai, Michael and Wang, Fei Fei and Weeks, Daniel E and Yanek, Lisa R and Wilson, James G and Abecasis, Goncalo and Arnett, Donna K and Becker, Lewis C and Blangero, John and Boerwinkle, Eric and Bowden, Donald W and Chang, Yi-Cheng and Chen, Yii-der I and Choi, Won Jung and Correa, Adolfo and Curran, Joanne E and Daly, Mark J and Dutcher, Susan K and Ellinor, Patrick T and Fornage, Myriam and Freedman, Barry I and Gabriel, Stacey and Germer, Soren and Gibbs, Richard A and He, Jiang and Hveem, Kristian and Jarvik, Gail P and Kaplan, Robert C and Kardia, Sharon L R and Kenny, Eimear and Kim, Ryan W and Kooperberg, Charles and Laurie, Cathy C and Lee, Seonwook and Lloyd-Jones, Don M and Loos, Ruth J F and Lubitz, Steven A and Mathias, Rasika A and Martinez, Karine A Viaud and McGarvey, Stephen T and Mitchell, Braxton D and Nickerson, Deborah A and North, Kari E and Palotie, Aarno and Park, Cheol Joo and Psaty, Bruce M and Rao, D C and Redline, Susan and Reiner, Alexander P and Seo, Daekwan and Seo, Jeong-Sun and Smith, Albert V and Tracy, Russell P and Vasan, Ramachandran S and Kathiresan, Sekar and Cupples, L Adrienne and Rotter, Jerome I and Morrison, Alanna C and Rich, Stephen S and Ripatti, Samuli and Willer, Cristen and Peloso, Gina M} } @article {8714, title = {Multi-ancestry genome-wide gene-sleep interactions identify novel loci for blood pressure.}, journal = {Mol Psychiatry}, year = {2021}, month = {2021 Apr 15}, abstract = {

Long and short sleep duration are associated with elevated blood pressure (BP), possibly through effects on molecular pathways that influence neuroendocrine and vascular systems. To gain new insights into the genetic basis of sleep-related BP variation, we performed genome-wide gene by short or long sleep duration interaction analyses on four BP traits (systolic BP, diastolic BP, mean arterial pressure, and pulse pressure) across five ancestry groups in two stages using 2 degree of freedom (df) joint test followed by 1df test of interaction effects. Primary multi-ancestry analysis in 62,969 individuals in stage 1 identified three novel gene by sleep interactions that were replicated in an additional 59,296 individuals in stage 2 (stage 1 + 2 P < 5 {\texttimes} 10), including rs7955964 (FIGNL2/ANKRD33) that increases BP among long sleepers, and rs73493041 (SNORA26/C9orf170) and rs10406644 (KCTD15/LSM14A) that increase BP among short sleepers (P < 5 {\texttimes} 10). Secondary ancestry-specific analysis identified another novel gene by long sleep interaction at rs111887471 (TRPC3/KIAA1109) in individuals of African ancestry (P = 2 {\texttimes} 10). Combined stage 1 and 2 analyses additionally identified significant gene by long sleep interactions at 10 loci including MKLN1 and RGL3/ELAVL3 previously associated with BP, and significant gene by short sleep interactions at 10 loci including C2orf43 previously associated with BP (P < 10). 2df test also identified novel loci for BP after modeling sleep that has known functions in sleep-wake regulation, nervous and cardiometabolic systems. This study indicates that sleep and primary mechanisms regulating BP may interact to elevate BP level, suggesting novel insights into sleep-related BP regulation.

}, issn = {1476-5578}, doi = {10.1038/s41380-021-01087-0}, author = {Wang, Heming and Noordam, Raymond and Cade, Brian E and Schwander, Karen and Winkler, Thomas W and Lee, Jiwon and Sung, Yun Ju and Bentley, Amy R and Manning, Alisa K and Aschard, Hugues and Kilpel{\"a}inen, Tuomas O and Ilkov, Marjan and Brown, Michael R and Horimoto, Andrea R and Richard, Melissa and Bartz, Traci M and Vojinovic, Dina and Lim, Elise and Nierenberg, Jovia L and Liu, Yongmei and Chitrala, Kumaraswamynaidu and Rankinen, Tuomo and Musani, Solomon K and Franceschini, Nora and Rauramaa, Rainer and Alver, Maris and Zee, Phyllis C and Harris, Sarah E and van der Most, Peter J and Nolte, Ilja M and Munroe, Patricia B and Palmer, Nicholette D and Kuhnel, Brigitte and Weiss, Stefan and Wen, Wanqing and Hall, Kelly A and Lyytik{\"a}inen, Leo-Pekka and O{\textquoteright}Connell, Jeff and Eiriksdottir, Gudny and Launer, Lenore J and de Vries, Paul S and Arking, Dan E and Chen, Han and Boerwinkle, Eric and Krieger, Jose E and Schreiner, Pamela J and Sidney, Stephen and Shikany, James M and Rice, Kenneth and Chen, Yii-Der Ida and Gharib, Sina A and Bis, Joshua C and Luik, Annemarie I and Ikram, M Arfan and Uitterlinden, Andr{\'e} G and Amin, Najaf and Xu, Hanfei and Levy, Daniel and He, Jiang and Lohman, Kurt K and Zonderman, Alan B and Rice, Treva K and Sims, Mario and Wilson, Gregory and Sofer, Tamar and Rich, Stephen S and Palmas, Walter and Yao, Jie and Guo, Xiuqing and Rotter, Jerome I and Biermasz, Nienke R and Mook-Kanamori, Dennis O and Martin, Lisa W and Barac, Ana and Wallace, Robert B and Gottlieb, Daniel J and Komulainen, Pirjo and Heikkinen, Sami and M{\"a}gi, Reedik and Milani, Lili and Metspalu, Andres and Starr, John M and Milaneschi, Yuri and Waken, R J and Gao, Chuan and Waldenberger, Melanie and Peters, Annette and Strauch, Konstantin and Meitinger, Thomas and Roenneberg, Till and V{\"o}lker, Uwe and D{\"o}rr, Marcus and Shu, Xiao-Ou and Mukherjee, Sutapa and Hillman, David R and K{\"a}h{\"o}nen, Mika and Wagenknecht, Lynne E and Gieger, Christian and Grabe, Hans J and Zheng, Wei and Palmer, Lyle J and Lehtim{\"a}ki, Terho and Gudnason, Vilmundur and Morrison, Alanna C and Pereira, Alexandre C and Fornage, Myriam and Psaty, Bruce M and van Duijn, Cornelia M and Liu, Ching-Ti and Kelly, Tanika N and Evans, Michele K and Bouchard, Claude and Fox, Ervin R and Kooperberg, Charles and Zhu, Xiaofeng and Lakka, Timo A and Esko, T{\~o}nu and North, Kari E and Deary, Ian J and Snieder, Harold and Penninx, Brenda W J H and Gauderman, W James and Rao, Dabeeru C and Redline, Susan and van Heemst, Diana} } @article {8713, title = {A System for Phenotype Harmonization in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program.}, journal = {Am J Epidemiol}, year = {2021}, month = {2021 Apr 16}, abstract = {

Genotype-phenotype association studies often combine phenotype data from multiple studies to increase power. Harmonization of the data usually requires substantial effort due to heterogeneity in phenotype definitions, study design, data collection procedures, and data set organization. Here we describe a centralized system for phenotype harmonization that includes input from phenotype domain and study experts, quality control, documentation, reproducible results, and data sharing mechanisms. This system was developed for the National Heart, Lung and Blood Institute{\textquoteright}s Trans-Omics for Precision Medicine program, which is generating genomic and other omics data for >80 studies with extensive phenotype data. To date, 63 phenotypes have been harmonized across thousands of participants from up to 17 studies per phenotype (participants recruited 1948-2012). We discuss challenges in this undertaking and how they were addressed. The harmonized phenotype data and associated documentation have been submitted to National Institutes of Health data repositories for controlled-access by the scientific community. We also provide materials to facilitate future harmonization efforts by the community, which include (1) the code used to generate the 63 harmonized phenotypes, enabling others to reproduce, modify or extend these harmonizations to additional studies; and (2) results of labeling thousands of phenotype variables with controlled vocabulary terms.

}, issn = {1476-6256}, doi = {10.1093/aje/kwab115}, author = {Stilp, Adrienne M and Emery, Leslie S and Broome, Jai G and Buth, Erin J and Khan, Alyna T and Laurie, Cecelia A and Wang, Fei Fei and Wong, Quenna and Chen, Dongquan and D{\textquoteright}Augustine, Catherine M and Heard-Costa, Nancy L and Hohensee, Chancellor R and Johnson, William Craig and Juarez, Lucia D and Liu, Jingmin and Mutalik, Karen M and Raffield, Laura M and Wiggins, Kerri L and de Vries, Paul S and Kelly, Tanika N and Kooperberg, Charles and Natarajan, Pradeep and Peloso, Gina M and Peyser, Patricia A and Reiner, Alex P and Arnett, Donna K and Aslibekyan, Stella and Barnes, Kathleen C and Bielak, Lawrence F and Bis, Joshua C and Cade, Brian E and Chen, Ming-Huei and Correa, Adolfo and Cupples, L Adrienne and de Andrade, Mariza and Ellinor, Patrick T and Fornage, Myriam and Franceschini, Nora and Gan, Weiniu and Ganesh, Santhi K and Graffelman, Jan and Grove, Megan L and Guo, Xiuqing and Hawley, Nicola L and Hsu, Wan-Ling and Jackson, Rebecca D and Jaquish, Cashell E and Johnson, Andrew D and Kardia, Sharon L R and Kelly, Shannon and Lee, Jiwon and Mathias, Rasika A and McGarvey, Stephen T and Mitchell, Braxton D and Montasser, May E and Morrison, Alanna C and North, Kari E and Nouraie, Seyed Mehdi and Oelsner, Elizabeth C and Pankratz, Nathan and Rich, Stephen S and Rotter, Jerome I and Smith, Jennifer A and Taylor, Kent D and Vasan, Ramachandran S and Weeks, Daniel E and Weiss, Scott T and Wilson, Carla G and Yanek, Lisa R and Psaty, Bruce M and Heckbert, Susan R and Laurie, Cathy C} } @article {8920, title = {Whole-genome association analyses of sleep-disordered breathing phenotypes in the NHLBI TOPMed program.}, journal = {Genome Med}, volume = {13}, year = {2021}, month = {2021 08 26}, pages = {136}, abstract = {

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 {\texttimes} 10) 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.

}, issn = {1756-994X}, doi = {10.1186/s13073-021-00917-8}, author = {Cade, Brian E and Lee, Jiwon and Sofer, Tamar and Wang, Heming and Zhang, Man and Chen, Han and Gharib, Sina A and Gottlieb, Daniel J and Guo, Xiuqing and Lane, Jacqueline M and Liang, Jingjing and Lin, Xihong and Mei, Hao and Patel, Sanjay R and Purcell, Shaun M and Saxena, Richa and Shah, Neomi A and Evans, Daniel S and Hanis, Craig L and Hillman, David R and Mukherjee, Sutapa and Palmer, Lyle J and Stone, Katie L and Tranah, Gregory J and Abecasis, Goncalo R and Boerwinkle, Eric A and Correa, Adolfo and Cupples, L Adrienne and Kaplan, Robert C and Nickerson, Deborah A and North, Kari E and Psaty, Bruce M and Rotter, Jerome I and Rich, Stephen S and Tracy, Russell P and Vasan, Ramachandran S and Wilson, James G and Zhu, Xiaofeng and Redline, Susan} } @article {8975, title = {Rare coding variants in 35 genes associate with circulating lipid levels-A multi-ancestry analysis of 170,000 exomes.}, journal = {Am J Hum Genet}, volume = {109}, year = {2022}, month = {2022 01 06}, pages = {81-96}, abstract = {

Large-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency < 1\%) predicted damaging coding variation by using sequence data from >170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels; some of these genes have not been previously associated with lipid levels when using rare coding variation from population-based samples. We prioritize 32 genes in array-based genome-wide association study (GWAS) loci based on aggregations of rare coding variants; three (EVI5, SH2B3, and PLIN1) had no prior association of rare coding variants with lipid levels. Most of our associated genes showed evidence of association among multiple ancestries. Finally, we observed an enrichment of gene-based associations for low-density lipoprotein cholesterol drug target genes and for genes closest to GWAS index single-nucleotide polymorphisms (SNPs). Our results demonstrate that gene-based associations can be beneficial for drug target development and provide evidence that the gene closest to the array-based GWAS index SNP is often the functional gene for blood lipid levels.

}, keywords = {Alleles, Blood Glucose, Case-Control Studies, Computational Biology, Databases, Genetic, Diabetes Mellitus, Type 2, Exome, Genetic Predisposition to Disease, Genetic Variation, Genetics, Population, Genome-Wide Association Study, Humans, Lipid Metabolism, Lipids, Liver, Molecular Sequence Annotation, Multifactorial Inheritance, Open Reading Frames, Phenotype, Polymorphism, Single Nucleotide}, issn = {1537-6605}, doi = {10.1016/j.ajhg.2021.11.021}, author = {Hindy, George and Dornbos, Peter and Chaffin, Mark D and Liu, Dajiang J and Wang, Minxian and Selvaraj, Margaret Sunitha and Zhang, David and Park, Joseph and Aguilar-Salinas, Carlos A and Antonacci-Fulton, Lucinda and Ardissino, Diego and Arnett, Donna K and Aslibekyan, Stella and Atzmon, Gil and Ballantyne, Christie M and Barajas-Olmos, Francisco and Barzilai, Nir and Becker, Lewis C and Bielak, Lawrence F and Bis, Joshua C and Blangero, John and Boerwinkle, Eric and Bonnycastle, Lori L and Bottinger, Erwin and Bowden, Donald W and Bown, Matthew J and Brody, Jennifer A and Broome, Jai G and Burtt, Noel P and Cade, Brian E and Centeno-Cruz, Federico and Chan, Edmund and Chang, Yi-Cheng and Chen, Yii-der I and Cheng, Ching-Yu and Choi, Won Jung and Chowdhury, Rajiv and Contreras-Cubas, Cecilia and C{\'o}rdova, Emilio J and Correa, Adolfo and Cupples, L Adrienne and Curran, Joanne E and Danesh, John and de Vries, Paul S and DeFronzo, Ralph A and Doddapaneni, Harsha and Duggirala, Ravindranath and Dutcher, Susan K and Ellinor, Patrick T and Emery, Leslie S and Florez, Jose C and Fornage, Myriam and Freedman, Barry I and Fuster, Valentin and Garay-Sevilla, Ma Eugenia and Garc{\'\i}a-Ortiz, Humberto and Germer, Soren and Gibbs, Richard A and Gieger, Christian and Glaser, Benjamin and Gonzalez, Clicerio and Gonzalez-Villalpando, Maria Elena and Graff, Mariaelisa and Graham, Sarah E and Grarup, Niels and Groop, Leif C and Guo, Xiuqing and Gupta, Namrata and Han, Sohee and Hanis, Craig L and Hansen, Torben and He, Jiang and Heard-Costa, Nancy L and Hung, Yi-Jen and Hwang, Mi Yeong and Irvin, Marguerite R and Islas-Andrade, Sergio and Jarvik, Gail P and Kang, Hyun Min and Kardia, Sharon L R and Kelly, Tanika and Kenny, Eimear E and Khan, Alyna T and Kim, Bong-Jo and Kim, Ryan W and Kim, Young Jin and Koistinen, Heikki A and Kooperberg, Charles and Kuusisto, Johanna and Kwak, Soo Heon and Laakso, Markku and Lange, Leslie A and Lee, Jiwon and Lee, Juyoung and Lee, Seonwook and Lehman, Donna M and Lemaitre, Rozenn N and Linneberg, Allan and Liu, Jianjun and Loos, Ruth J F and Lubitz, Steven A and Lyssenko, Valeriya and Ma, Ronald C W and Martin, Lisa Warsinger and Mart{\'\i}nez-Hern{\'a}ndez, Ang{\'e}lica and Mathias, Rasika A and McGarvey, Stephen T and McPherson, Ruth and Meigs, James B and Meitinger, Thomas and Melander, Olle and Mendoza-Caamal, Elvia and Metcalf, Ginger A and Mi, Xuenan and Mohlke, Karen L and Montasser, May E and Moon, Jee-Young and Moreno-Macias, Hortensia and Morrison, Alanna C and Muzny, Donna M and Nelson, Sarah C and Nilsson, Peter M and O{\textquoteright}Connell, Jeffrey R and Orho-Melander, Marju and Orozco, Lorena and Palmer, Colin N A and Palmer, Nicholette D and Park, Cheol Joo and Park, Kyong Soo and Pedersen, Oluf and Peralta, Juan M and Peyser, Patricia A and Post, Wendy S and Preuss, Michael and Psaty, Bruce M and Qi, Qibin and Rao, D C and Redline, Susan and Reiner, Alexander P and Revilla-Monsalve, Cristina and Rich, Stephen S and Samani, Nilesh and Schunkert, Heribert and Schurmann, Claudia and Seo, Daekwan and Seo, Jeong-Sun and Sim, Xueling and Sladek, Rob and Small, Kerrin S and So, Wing Yee and Stilp, Adrienne M and Tai, E Shyong and Tam, Claudia H T and Taylor, Kent D and Teo, Yik Ying and Thameem, Farook and Tomlinson, Brian and Tsai, Michael Y and Tuomi, Tiinamaija and Tuomilehto, Jaakko and Tusi{\'e}-Luna, Teresa and Udler, Miriam S and van Dam, Rob M and Vasan, Ramachandran S and Viaud Martinez, Karine A and Wang, Fei Fei and Wang, Xuzhi and Watkins, Hugh and Weeks, Daniel E and Wilson, James G and Witte, Daniel R and Wong, Tien-Yin and Yanek, Lisa R and Kathiresan, Sekar and Rader, Daniel J and Rotter, Jerome I and Boehnke, Michael and McCarthy, Mark I and Willer, Cristen J and Natarajan, Pradeep and Flannick, Jason A and Khera, Amit V and Peloso, Gina M} } @article {9101, title = {Targeted Genome Sequencing Identifies Multiple Rare Variants in Caveolin-1 Associated with Obstructive Sleep Apnea.}, journal = {Am J Respir Crit Care Med}, year = {2022}, month = {2022 Jul 13}, abstract = {

INTRODUCTION: Obstructive sleep apnea (OSA) is a common disorder associated with increased risk for cardiovascular disease, diabetes, and premature mortality. There is strong clinical and epi-demiologic evidence supporting the importance of genetic factors influencing OSA, but limited data implicating specific genes.

METHODS: Leveraging high depth genomic sequencing data from the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program and imputed genotype data from multiple population-based studies, we performed linkage analysis in the Cleve-land Family Study (CFS) followed by multi-stage gene-based association analyses in independent cohorts to search for rare variants contributing to OSA severity as assessed by the apnea-hypopnea index (AHI) in a total of 7,708 individuals of European ancestry.

RESULTS: Linkage analysis in CFS identified a suggestive linkage peak on chromosome 7q31 (LOD=2.31). Gene-based analysis identified 21 non-coding rare variants in Caveolin-1 (CAV1) associated with lower AHI after accounting for multiple comparisons (p=7.4{\texttimes}10-8). These non-coding variants together significantly contributed to the linkage evidence (p<10-3). Follow-up anal-ysis 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).

CONCLUSION: 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.

}, issn = {1535-4970}, doi = {10.1164/rccm.202203-0618OC}, author = {Liang, Jingjing and Wang, Heming and Cade, Brian E and Kurniansyah, Nuzulul and He, Karen Y and Lee, Jiwon and Sands, Scott A and Brody, Jennifer and Chen, Han and Gottlieb, Daniel J and Evans, Daniel S and Guo, Xiuqing and Gharib, Sina A and Hale, Lauren and Hillman, David R and Lutsey, Pamela L and Mukherjee, Sutapa and Ochs-Balcom, Heather M and Palmer, Lyle J and Purcell, Shaun and Saxena, Richa and Patel, Sanjay R and Stone, Katie L and Tranah, Gregory J and Boerwinkle, Eric and Lin, Xihong and Liu, Yongmei and Psaty, Bruce M and Vasan, Ramachandran S and Manichaikul, Ani and Rich, Stephen S and Rotter, Jerome I and Sofer, Tamar and Redline, Susan and Zhu, Xiaofeng} } @article {9449, title = {Whole genome analysis of plasma fibrinogen reveals population-differentiated genetic regulators with putative liver roles.}, journal = {medRxiv}, year = {2023}, month = {2023 Jun 12}, abstract = {

UNLABELLED: Genetic studies have identified numerous regions associated with plasma fibrinogen levels in Europeans, yet missing heritability and limited inclusion of non-Europeans necessitates further studies with improved power and sensitivity. Compared with array-based genotyping, whole genome sequencing (WGS) data provides better coverage of the genome and better representation of non-European variants. To better understand the genetic landscape regulating plasma fibrinogen levels, we meta-analyzed WGS data from the NHLBI{\textquoteright}s Trans-Omics for Precision Medicine (TOPMed) program (n=32,572), with array-based genotype data from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium (n=131,340) imputed to the TOPMed or Haplotype Reference Consortium panel. We identified 18 loci that have not been identified in prior genetic studies of fibrinogen. Of these, four are driven by common variants of small effect with reported MAF at least 10\% higher in African populations. Three ( , and signals contain predicted deleterious missense variants. Two loci, and , each harbor two conditionally distinct, non-coding variants. The gene region encoding the protein chain subunits ( ), contains 7 distinct signals, including one novel signal driven by rs28577061, a variant common (MAF=0.180) in African reference panels but extremely rare (MAF=0.008) in Europeans. Through phenome-wide association studies in the VA Million Veteran Program, we found associations between fibrinogen polygenic risk scores and thrombotic and inflammatory disease phenotypes, including an association with gout. Our findings demonstrate the utility of WGS to augment genetic discovery in diverse populations and offer new insights for putative mechanisms of fibrinogen regulation.

KEY POINTS: Largest and most diverse genetic study of plasma fibrinogen identifies 54 regions (18 novel), housing 69 conditionally distinct variants (20 novel).Sufficient power achieved to identify signal driven by African population variant.Links to (1) liver enzyme, blood cell and lipid genetic signals, (2) liver regulatory elements, and (3) thrombotic and inflammatory disease.

}, doi = {10.1101/2023.06.07.23291095}, author = {Huffman, Jennifer E and Nicolas, Jayna and Hahn, Julie and Heath, Adam S and Raffield, Laura M and Yanek, Lisa R and Brody, Jennifer A and Thibord, Florian and Almasy, Laura and Bartz, Traci M and Bielak, Lawrence F and Bowler, Russell P and Carrasquilla, Germ{\'a}n D and Chasman, Daniel I and Chen, Ming-Huei and Emmert, David B and Ghanbari, Mohsen and Haessle, Jeffery and Hottenga, Jouke-Jan and Kleber, Marcus E and Le, Ngoc-Quynh and Lee, Jiwon and Lewis, Joshua P and Li-Gao, Ruifang and Luan, Jian{\textquoteright}an and Malmberg, Anni and Mangino, Massimo and Marioni, Riccardo E and Martinez-Perez, Angel and Pankratz, Nathan and Polasek, Ozren and Richmond, Anne and Rodriguez, Benjamin At and Rotter, Jerome I and Steri, Maristella and Suchon, Pierre and Trompet, Stella and Weiss, Stefan and Zare, Marjan and Auer, Paul and Cho, Michael H and Christofidou, Paraskevi and Davies, Gail and de Geus, Eco and Deleuze, Jean-Francois and Delgado, Graciela E and Ekunwe, Lynette and Faraday, Nauder and G{\"o}gele, Martin and Greinacher, Andreas and He, Gao and Howard, Tom and Joshi, Peter K and Kilpel{\"a}inen, Tuomas O and Lahti, Jari and Linneberg, Allan and Naitza, Silvia and Noordam, Raymond and Pa{\"u}ls-Verg{\'e}s, Ferran and Rich, Stephen S and Rosendaal, Frits R and Rudan, Igor and Ryan, Kathleen A and Souto, Juan Carlos and van Rooij, Frank Ja and Wang, Heming and Zhao, Wei and Becker, Lewis C and Beswick, Andrew and Brown, Michael R and Cade, Brian E and Campbell, Harry and Cho, Kelly and Crapo, James D and Curran, Joanne E and de Maat, Moniek Pm and Doyle, Margaret and Elliott, Paul and Floyd, James S and Fuchsberger, Christian and Grarup, Niels and Guo, Xiuqing and Harris, Sarah E and Hou, Lifang and Kolcic, Ivana and Kooperberg, Charles and Menni, Cristina and Nauck, Matthias and O{\textquoteright}Connell, Jeffrey R and Orr{\`u}, Valeria and Psaty, Bruce M and R{\"a}ikk{\"o}nen, Katri and Smith, Jennifer A and Soria, Jos{\'e} Manuel and Stott, David J and van Hylckama Vlieg, Astrid and Watkins, Hugh and Willemsen, Gonneke and Wilson, Peter and Ben-Shlomo, Yoav and Blangero, John and Boomsma, Dorret and Cox, Simon R and Dehghan, Abbas and Eriksson, Johan G and Fiorillo, Edoardo and Fornage, Myriam and Hansen, Torben and Hayward, Caroline and Ikram, M Arfan and Jukema, J Wouter and Kardia, Sharon Lr and Lange, Leslie A and M{\"a}rz, Winfried and Mathias, Rasika A and Mitchell, Braxton D and Mook-Kanamori, Dennis O and Morange, Pierre-Emmanuel and Pedersen, Oluf and Pramstaller, Peter P and Redline, Susan and Reiner, Alexander and Ridker, Paul M and Silverman, Edwin K and Spector, Tim D and V{\"o}lker, Uwe and Wareham, Nick and Wilson, James F and Yao, Jie and Tr{\'e}gou{\"e}t, David-Alexandre and Johnson, Andrew D and Wolberg, Alisa S and de Vries, Paul S and Sabater-Lleal, Maria and Morrison, Alanna C and Smith, Nicholas L} } @article {9861, title = {Gene-Excessive Sleepiness Interactions Suggest Treatment Targets for Obstructive Sleep Apnea Subtype.}, journal = {medRxiv}, year = {2024}, month = {2024 Oct 28}, abstract = {

Obstructive sleep apnea (OSA) is a multifactorial sleep disorder characterized by a strong genetic basis. Excessive daytime sleepiness (EDS) is a symptom that is reported by a subset of OSA patients, persisting even after treatment with continuous positive airway pressure (CPAP). It is recognized as a clinical subtype underlying OSA carrying alarming heightened cardiovascular risk. Thus, conceptualizing EDS as an exposure variable, we sought to investigate EDS{\textquoteright}s influence on genetic variation linked to apnea-hypopnea index (AHI), a diagnostic measure of OSA severity. This study serves as the first large-scale genome-wide gene x environment interaction analysis for AHI, investigating the interplay between its genetic markers and EDS across and within specific sex. Our work pools together whole genome sequencing data from seven cohorts, enabling a diverse dataset (four population backgrounds) of over 11,500 samples. Among the total 16 discovered genetic targets with interaction evidence with EDS, eight are previously unreported for OSA, including , , and identified in all sexes; , , and identified in males; and and identified in females. We discuss connections to insulin resistance, thiamine deficiency, and resveratrol use that may be worthy of therapeutic consideration for excessively sleepy OSA patients.

}, doi = {10.1101/2024.10.25.24316158}, author = {Nagarajan, Pavithra and Kurniansyah, Nuzulul and Lee, Jiwon and Gharib, Sina A and Xu, Yushan and Zhang, Yiyan and Spitzer, Brian and Faquih, Tariq and Zhou, Hufeng and Boerwinkle, Eric and Chen, Han and Gottlieb, Daniel J and Guo, Xiuqing and Heard-Costa, Nancy L and Hidalgo, Bertha A and Levy, Daniel and Liu, Peter Y and Mei, Hao and Montalvan, Rebecca and Mukherjee, Sutapa and North, Kari E and O{\textquoteright}Conner, George T and Palmer, Lyle J and Patel, Sanjay R and Psaty, Bruce M and Purcell, Shaun M and Raffield, Laura M and Rich, Stephen S and Rotter, Jerome I and Saxena, Richa and Smith, Albert V and Stone, Katie L and Zhu, Xiaofeng and Cade, Brian E and Sofer, Tamar and Redline, Susan and Wang, Heming} }