Browsing by Author "Alonso, Alvaro"
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Item Advancing Research on the Complex Interrelations between Atrial fibrillation and Heart Failure: A Report from a National Heart, Lung, and Blood Institute Virtual Workshop(American Heart Association, 2020-06-09) Al-Khatib, Sana M.; Benjamin, Emelia J.; Albert, Christine M.; Alonso, Alvaro; Chauhan, Cynthia; Chen, Peng-Sheng; Curtis, Anne B.; Desvigne-Nickens, Patrice; Ho, Jennifer E.; Lam, Carolyn S.P.; Link, Mark S.; Patton, Kristen K.; Redfield, Margaret M.; Rienstra, Michiel; Rosenberg, Yves; Schnabel, Renate; Spertus, John A.; Warner Stevenson, Lynne; Hills, Mellanie True; Voors, Adriaan A.; Cooper, Lawton S.; Go, Alan S.; Medicine, School of MedicineThe interrelationships between atrial fibrillation (AF) and heart failure (HF) are complex and poorly understood, yet the number of patients with AF and HF continues to increase worldwide. Thus, there is a need for initiatives that prioritize research on the intersection between AF and HF. This report summarizes the proceedings of a virtual workshop convened by the National Heart, Lung, and Blood Institute to identify important research opportunities in AF and HF. Key knowledge gaps were reviewed and research priorities were proposed for characterizing the pathophysiological overlap and deleterious interactions between AF and HF; preventing HF in persons with AF; preventing AF in individuals with HF; and addressing symptom burden and health status outcomes in AF and HF. These research priorities will hopefully help inform, encourage, and stimulate innovative, cost-efficient, and transformative studies to enhance the outcomes of patients with AF and HF.Item Ankle-Brachial Index and Risk of Sudden Cardiac Death in the Community: The ARIC Study(American Heart Association, 2024) Suzuki, Takeki; Zhu, Xiaoqian; Adabag, Selcuk; Matsushita, Kunihiro; Butler, Kenneth R.; Griswold, Michael E.; Alonso, Alvaro; Rosamond, Wayne; Sotoodehnia, Nona; Mosley, Thomas H.; Medicine, School of MedicineBackground: Sudden cardiac death (SCD) is a significant global public health problem accounting for 15% to 20% of all deaths. A great majority of SCD is associated with coronary heart disease, which may first be detected at autopsy. The ankle-brachial index (ABI) is a simple, noninvasive measure of subclinical atherosclerosis. The purpose of this study was to examine the relationship between ABI and SCD in a middle-aged biracial general population. Methods and results: Participants of the ARIC (Atherosclerosis Risk in Communities) study with an ABI measurement between 1987 and 1989 were included. ABI was categorized as low (≤0.90), borderline (0.90-1.00), normal (1.00-1.40), and noncompressible (>1.40). SCD was defined as a sudden pulseless condition presumed to be caused by a ventricular tachyarrhythmia in a previously stable individual and was adjudicated by a committee of cardiac electrophysiologists, cardiologists, and internists. Cox proportional hazards models were used to evaluate the associations between baseline ABI and incident SCD. Of the 15 081 participants followed for a median of 23.5 years, 556 (3.7%) developed SCD (1.96 cases per 1000 person-years). Low and borderline ABIs were associated with an increased risk of SCD (demographically adjusted hazard ratios [ HRs ], 2.27 [ 95% CI, 1.64-3.14 ] and 1.52 [ 95% CI, 1.17-1.96 ], respectively) compared with normal ABI. The association between low ABI and SCD remained significant after adjustment for traditional cardiovascular risk factors (HR, 1.63 [ 95% CI, 1.15-2.32 ]). Conclusions: Low ABI is independently associated with an increased risk of SCD in a middle-aged biracial general population. ABI could be incorporated into future SCD risk prediction models.Item Exploring Factors Contributing to Caregiver Burden in Family Caregivers of Congolese Adults with Suspected Dementia(Wiley, 2023) Ikanga, Jean; Reyes, Anny; Zhao, Liping; Hill-Jarrett, Tanisha G.; Hammers, Dustin; Epenge, Emmanuel; Esambo, Herve; Kavugho, Immaculée; Esselakoy, Christian; Gikelekele, Guy; Tshengele, Nathan; Alonso, Alvaro; Robinson-Lane, Sheria G.; Neurology, School of MedicineIntroduction: Predicting caregiver burden in individuals with suspected dementia - is critical due to the debilitating nature of these disorders and need for caregiver support. While some examination of the factors affecting burden has been undertaken in Sub-Saharan Africa, each country presents with its own unique challenges and obstacles. This pilot study investigates predictors of caregiver burden in family caregivers of individuals with suspected dementia living in the Democratic Republic of the Congo (DRC). Methods: Linear and multiple regression analyses were conducted to explore factors associated with caregiver burden in 30 patient-caregiver dyads with the Zarit Burden Interview (ZBI) for caregiver burden evaluation. Cognitive impairments of patients were assessed using the Community Screening Instrument for Dementia, Alzheimer's Questionnaire (AQ), the African Neuropsychology Battery, and the Neuropsychiatric Symptoms Inventory (NPI). Results: Average caregiver burden on the ZBI was 36.1 (SD = 14.6; range = 12-58). Greater impairments in patient cognition (orientation, visuospatial, memory, executive functioning), fragility, and neuropsychiatric symptoms (delirium, agitation, depression) were predictive of caregiver burden. After controlling for AQ scores and caregiver gender, greater symptoms of depression, and worse performances on verbal memory and problem solving were associated with greater caregiver burden. Conclusion: Worsening patient fragility, cognition, functioning, and neuropsychiatric symptoms influenced caregiver burden in caregivers of individuals with suspected cognitive impairment in the DRC. These findings are consistent with the prior literature. Future studies may wish to explore supportive factors and caregiver specific characteristics that buffer against perceived burden.Item Investigating Gene-Diet Interactions Impacting the Association Between Macronutrient Intake and Glycemic Traits(American Diabetes Association, 2023) Westerman, Kenneth E.; Walker, Maura E.; Gaynor, Sheila M.; Wessel, Jennifer; DiCorpo, Daniel; Ma, Jiantao; Alonso, Alvaro; Aslibekyan, Stella; Baldridge, Abigail S.; Bertoni, Alain G.; Biggs, Mary L.; Brody, Jennifer A.; Chen, Yii-Der Ida; Dupuis, Joseé; Goodarzi, Mark O.; Guo, Xiuqing; Hasbani, Natalie R.; Heath, Adam; Hidalgo, Bertha; Irvin, Marguerite R.; Johnson, W. Craig; Kalyani, Rita R.; Lange, Leslie; Lemaitre, Rozenn N.; Liu, Ching-Ti; Liu, Simin; Moon, Jee-Young; Nassir, Rami; Pankow, James S.; Pettinger, Mary; Raffield, Laura M.; Rasmussen-Torvik, Laura J.; Selvin, Elizabeth; Senn, Mackenzie K.; Shadyab, Aladdin H.; Smith, Albert V.; Smith, Nicholas L.; Steffen, Lyn; Talegakwar, Sameera; Taylor, Kent D.; de Vries, Paul S.; Wilson, James G.; Wood, Alexis C.; Yanek, Lisa R.; Yao, Jie; Zheng, Yinan; Boerwinkle, Eric; Morrison, Alanna C.; Fornage, Miriam; Russell, Tracy P.; Psaty, Bruce M.; Levy, Daniel; Heard-Costa, Nancy L.; Ramachandran, Vasan S.; Mathias, Rasika A.; Arnett, Donna K.; Kaplan, Robert; North, Kari E.; Correa, Adolfo; Carson, April; Rotter, Jerome I.; Rich, Stephen S.; Manson, JoAnn E.; Reiner, Alexander P.; Kooperberg, Charles; Florez, Jose C.; Meigs, James B.; Merino, Jordi; Tobias, Deirdre K.; Chen, Han; Manning, Alisa K.; Epidemiology, Richard M. Fairbanks School of Public HealthFew studies have demonstrated reproducible gene-diet interactions (GDIs) impacting metabolic disease risk factors, likely due in part to measurement error in dietary intake estimation and insufficient capture of rare genetic variation. We aimed to identify GDIs across the genetic frequency spectrum impacting the macronutrient-glycemia relationship in genetically and culturally diverse cohorts. We analyzed 33,187 participants free of diabetes from 10 National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine program cohorts with whole-genome sequencing, self-reported diet, and glycemic trait data. We fit cohort-specific, multivariable-adjusted linear mixed models for the effect of diet, modeled as an isocaloric substitution of carbohydrate for fat, and its interactions with common and rare variants genome-wide. In main effect meta-analyses, participants consuming more carbohydrate had modestly lower glycemic trait values (e.g., for glycated hemoglobin [HbA1c], -0.013% HbA1c/250 kcal substitution). In GDI meta-analyses, a common African ancestry-enriched variant (rs79762542) reached study-wide significance and replicated in the UK Biobank cohort, indicating a negative carbohydrate-HbA1c association among major allele homozygotes only. Simulations revealed that >150,000 samples may be necessary to identify similar macronutrient GDIs under realistic assumptions about effect size and measurement error. These results generate hypotheses for further exploration of modifiable metabolic disease risk in additional cohorts with African ancestry. Article highlights: We aimed to identify genetic modifiers of the dietary macronutrient-glycemia relationship using whole-genome sequence data from 10 Trans-Omics for Precision Medicine program cohorts. Substitution models indicated a modest reduction in glycemia associated with an increase in dietary carbohydrate at the expense of fat. Genome-wide interaction analysis identified one African ancestry-enriched variant near the FRAS1 gene that may interact with macronutrient intake to influence hemoglobin A1c. Simulation-based power calculations accounting for measurement error suggested that substantially larger sample sizes may be necessary to discover further gene-macronutrient interactions.Item Prevalence of Suspected Dementia in a Sample of Adults Living in Kinshasa-Democratic Republic of the Congo(Wiley, 2023) Ikanga, Jean; Reyes, Anny; Kaba, Didine; Akilimali, Pierre; Mampunza, Samuel; Epenge, Emmanuel; Gikelekele, Guy; Kavugho, Immaculee; Tshengele, Nathan; Hammers, Dustin B.; Alonso, Alvaro; Neurology, School of MedicineBackground: The prevalence of dementia in Sub-Saharan Africa, particularly in French-speaking countries, has received limited attention. This study investigates the prevalence and risk factors of suspected dementia in elderly adults in Kinshasa, Democratic Republic of the Congo (DRC). Methods: A community-based sample of 355 individuals over 65 years old was selected using multistage probability sampling in Kinshasa. Participants were screened using the Community Screening Instrument for Dementia, Alzheimer's Questionnaire, Geriatric Depression Scale, Beck Anxiety Inventory, and Individual Fragility Questionnaire, followed by clinical interview and neurological examination. Suspected dementia diagnoses were made based on the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) criteria including significant cognitive and functional impairments. Prevalence and odds ratios (ORs) with 95% confidence interval (CI) were calculated using, respectively, regression and logistic regression. Results: Among 355 participants (mean age 74, SD = 7; 51% male), the crude prevalence of suspected dementia was 6.2% (9.0% in women and 3.8% in men). Female sex was a significant factor associated with suspected dementia [OR = 2.81, 95% CI (1.08-7.41)]. The prevalence of dementia increased with age (14.0% after 75 years and 23.1% after 85 years), with age being significantly associated with suspected dementia [OR = 5.42, 95% CI (2.86-10.28)]. Greater education was associated with a lower prevalence of suspected dementia [OR = 2.36, 95% CI (2.14-2.94), comparing those with ≥7.3 years of education to those with <7.3 years of education]. Other factors associated with the prevalence of suspected dementia included being widowed (OR = 1.66, 95% CI (1.05-2.61), being retired or semi-retired (OR = 3.25, 95% CI (1.50-7.03)], a diagnosis of anxiety [OR = 2.56, 95% CI (1.05-6.13)], and death of a spouse or a relative after age 65 [OR = 1.73, 95% CI (1.58-1.92)]. In contrast, depression [OR = 1.92, 95% CI (0.81-4.57)], hypertension [OR = 1.16, 95% CI (0.79-1.71)], body mass index (BMI) [OR = 1.06, 95% CI (0.40-2.79)], and alcohol consumption [OR = 0.83, 95% CI (0.19-3.58)] were not significantly associated with suspected dementia. Conclusions: This study found a prevalence of suspected dementia in Kinshasa/DRC similar to other developing countries and Central African countries. Reported risk factors provide information to identify high-risk individuals and develop preventive strategies in this setting.Item Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program(Springer Nature, 2021) Taliun, Daniel; Harris, Daniel N.; Kessler, Michael D.; Carlson, Jedidiah; Szpiech, Zachary A.; Torres, Raul; Gagliano Taliun, Sarah A.; Corvelo, André; Gogarten, Stephanie M.; Kang, Hyun Min; Pitsillides, Achilleas N.; LeFaive, Jonathon; Lee, Seung-Been; Tian, Xiaowen; Browning, Brian L.; Das, Sayantan; Emde, Anne-Katrin; Clarke, Wayne E.; Loesch, Douglas P.; Shetty, Amol C.; Blackwell, Thomas W.; Smith, Albert V.; Wong, Quenna; Liu, Xiaoming; Conomos, Matthew P.; Bobo, Dean M.; Aguet, François; Albert, Christine; Alonso, Alvaro; Ardlie, Kristin G.; Arking, Dan E.; Aslibekyan, Stella; Auer, Paul L.; Barnard, John; Barr, R. Graham; Barwick, Lucas; Becker, Lewis C.; Beer, Rebecca L.; Benjamin, Emelia J.; Bielak, Lawrence F.; Blangero, John; Boehnke, Michael; Bowden, Donald W.; Brody, Jennifer A.; Burchard, Esteban G.; Cade, Brian E.; Casella, James F.; Chalazan, Brandon; Chasman, Daniel I.; Chen, Yii-Der Ida; Cho, Michael H.; Choi, Seung Hoan; Chung, Mina K.; Clish, Clary B.; Correa, Adolfo; Curran, Joanne E.; Custer, Brian; Darbar, Dawood; Daya, Michelle; de Andrade, Mariza; DeMeo, Dawn L.; Dutcher, Susan K.; Ellinor, Patrick T.; Emery, Leslie S.; Eng, Celeste; Fatkin, Diane; Fingerlin, Tasha; Forer, Lukas; Fornage, Myriam; Franceschini, Nora; Fuchsberger, Christian; Fullerton, Stephanie M.; Germer, Soren; Gladwin, Mark T.; Gottlieb, Daniel J.; Guo, Xiuqing; Hall, Michael E.; He, Jiang; Heard-Costa, Nancy L.; Heckbert, Susan R.; Irvin, Marguerite R.; Johnsen, Jill M.; Johnson, Andrew D.; Kaplan, Robert; Kardia, Sharon L. R.; Kelly, Tanika; Kelly, Shannon; Kenny, Eimear E.; Kiel, Douglas P.; Klemmer, Robert; Konkle, Barbara A.; Kooperberg, Charles; Köttgen, Anna; Lange, Leslie A.; Lasky-Su, Jessica; Levy, Daniel; Lin, Xihong; Lin, Keng-Han; Liu, Chunyu; Loos, Ruth J. F.; Garman, Lori; Gerszten, Robert; Lubitz, Steven A.; Lunetta, Kathryn L.; Mak, Angel C. Y.; Manichaikul, Ani; Manning, Alisa K.; Mathias, Rasika A.; McManus, David D.; McGarvey, Stephen T.; Meigs, James B.; Meyers, Deborah A.; Mikulla, Julie L.; Minear, Mollie A.; Mitchell, Braxton D.; Mohanty, Sanghamitra; Montasser, May E.; Montgomery, Courtney; Morrison, Alanna C.; Murabito, Joanne M.; Natale, Andrea; Natarajan, Pradeep; Nelson, Sarah C.; North, Kari E.; O'Connell, Jeffrey R.; Palmer, Nicholette D.; Pankratz, Nathan; Peloso, Gina M.; Peyser, Patricia A.; Pleiness, Jacob; Post, Wendy S.; Psaty, Bruce M.; Rao, D. C.; Redline, Susan; Reiner, Alexander P.; Roden, Dan; Rotter, Jerome I.; Ruczinski, Ingo; Sarnowski, Chloé; Schoenherr, Sebastian; Schwartz, David A.; Seo, Jeong-Sun; Seshadri, Sudha; Sheehan, Vivien A.; Sheu, Wayne H.; Shoemaker, M. Benjamin; Smith, Nicholas L.; Smith, Jennifer A.; Sotoodehnia, Nona; Stilp, Adrienne M.; Tang, Weihong; Taylor, Kent D.; Telen, Marilyn; Thornton, Timothy A.; Tracy, Russell P.; Van Den Berg, David J.; Vasan, Ramachandran S.; Viaud-Martinez, Karine A.; Vrieze, Scott; Weeks, Daniel E.; Weir, Bruce S.; Weiss, Scott T.; Weng, Lu-Chen; Willer, Cristen J.; Zhang, Yingze; Zhao, Xutong; Arnett, Donna K.; Ashley-Koch, Allison E.; Barnes, Kathleen C.; Boerwinkle, Eric; Gabriel, Stacey; Gibbs, Richard; Rice, Kenneth M.; Rich, Stephen S.; Silverman, Edwin K.; Qasba, Pankaj; Gan, Weiniu; NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium; Papanicolaou, George J.; Nickerson, Deborah A.; Browning, Sharon R.; Zody, Michael C.; Zöllner, Sebastian; Wilson, James G.; Cupples, L. Adrienne; Laurie, Cathy C.; Jaquish, Cashell E.; Hernandez, Ryan D.; O'Connor, Timothy D.; Abecasis, Gonçalo R.; Epidemiology, Richard M. Fairbanks School of Public HealthThe Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%.Item Whole Genome Sequence Association Analysis of Fasting Glucose and Fasting Insulin Levels in Diverse Cohorts from the NHLBI TOPMed Program(Springer Nature, 2022-07-28) DiCorpo, Daniel; Gaynor, Sheila M.; Russell, Emily M.; Westerman, Kenneth E.; Raffield, Laura M.; Majarian, Timothy D.; Wu, Peitao; Sarnowski, Chloé; Highland, Heather M.; Jackson, Anne; Hasbani, Natalie R.; de Vries, Paul S.; Brody, Jennifer A.; Hidalgo, Bertha; Guo, Xiuqing; Perry, James A.; O’Connell, Jeffrey R.; Lent, Samantha; Montasser, May E.; Cade, Brian E.; Jain, Deepti; Wang, Heming; D’Oliveira Albanus, Ricardo; Varshney, Arushi; Yanek, Lisa R.; Lange, Leslie; Palmer, Nicholette D.; Almeida, Marcio; Peralta, Juan M.; Aslibekyan, Stella; Baldridge, Abigail S.; Bertoni, Alain G.; Bielak, Lawrence F.; Chen, Chung-Shiuan; Chen, Yii-Der Ida; Choi, Won Jung; Goodarzi, Mark O.; Floyd, James S.; Irvin, Marguerite R.; Kalyani, Rita R.; Kelly, Tanika N.; Lee, Seonwook; Liu, Ching-Ti; Loesch, Douglas; Manson, JoAnn E.; Minster, Ryan L.; Naseri, Take; Pankow, James S.; Rasmussen-Torvik, Laura J.; Reiner, Alexander P.; Reupena, Muagututi’a Sefuiva; Selvin, Elizabeth; Smith, Jennifer A.; Weeks, Daniel E.; Xu, Huichun; Yao, Jie; Zhao, Wei; Parker, Stephen; Alonso, Alvaro; Arnett, Donna K.; Blangero, John; Boerwinkle, Eric; Correa, Adolfo; Cupples, L. Adrienne; Curran, Joanne E.; Duggirala, Ravindranath; He, Jiang; Heckbert, Susan R.; Kardia, Sharon L.R.; Kim, Ryan W.; Kooperberg, Charles; Liu, Simin; Mathias, Rasika A.; McGarvey, Stephen T.; Mitchell, Braxton D.; Morrison, Alanna C.; Peyser, Patricia A.; Psaty, Bruce M.; Redline, Susan; Shuldiner, Alan R.; Taylor, Kent D.; Vasan, Ramachandran S.; Viaud-Martinez, Karine A.; Florez, Jose C.; Wilson, James G.; Sladek, Robert; Rich, Stephen S.; Rotter, Jerome I.; Lin, Xihong; Dupuis, Josée; Meigs, James B.; Wessel, Jennifer; Manning, Alisa K.; Epidemiology, School of Public HealthThe genetic determinants of fasting glucose (FG) and fasting insulin (FI) have been studied mostly through genome arrays, resulting in over 100 associated variants. We extended this work with high-coverage whole genome sequencing analyses from fifteen cohorts in NHLBI's Trans-Omics for Precision Medicine (TOPMed) program. Over 23,000 non-diabetic individuals from five race-ethnicities/populations (African, Asian, European, Hispanic and Samoan) were included. Eight variants were significantly associated with FG or FI across previously identified regions MTNR1B, G6PC2, GCK, GCKR and FOXA2. We additionally characterize suggestive associations with FG or FI near previously identified SLC30A8, TCF7L2, and ADCY5 regions as well as APOB, PTPRT, and ROBO1. Functional annotation resources including the Diabetes Epigenome Atlas were compiled for each signal (chromatin states, annotation principal components, and others) to elucidate variant-to-function hypotheses. We provide a catalog of nucleotide-resolution genomic variation spanning intergenic and intronic regions creating a foundation for future sequencing-based investigations of glycemic traits.