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Schooling CM, Terry MB. Interpreting disease genome-wide association studies and polygenetic risk scores given eligibility and study design considerations. Genet Epidemiol 2024; 48:468-472. [PMID: 38797991 DOI: 10.1002/gepi.22567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 04/10/2024] [Accepted: 04/16/2024] [Indexed: 05/29/2024]
Abstract
Genome-wide association studies (GWAS) have been helpful in identifying genetic variants predicting cancer risk and providing new insights into cancer biology. Increasing use of genetically informed care, as well as genetically informed prevention and treatment strategies, have also drawn attention to some of the inherent limitations of cancer genetic data. Specifically, genetic endowment is lifelong. However, those recruited into cancer studies tend to be middle-aged or older people, meaning the exposure most likely starts before recruitment, as opposed to exposure and recruitment aligning, as in a trial or a target trial. Studies in survivors can be biased as a result of depletion of the susceptibles, here specifically due to genetic vulnerability and the cancer of interest or a competing risk. In addition, including prevalent cases in a case-control study will make the genetics of survival with cancer look harmful (Neyman bias). Here, we describe ways of designing GWAS to maximize explanatory power and predictive utility, by reducing selection bias due to only recruiting survivors and reducing Neyman bias due to including prevalent cases alongside using other techniques, such as selection diagrams, age-stratification, and Mendelian randomization, to facilitate GWAS interpretability and utility.
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Affiliation(s)
- Catherine Mary Schooling
- Li Ka Shing Faculty of Medicine, School of Public Health, The University of Hong Kong, Hong Kong SAR, China
- Graduate School of Public Health and Health Policy, The City University of New York, New York City, New York, USA
| | - Mary Beth Terry
- Mailman School of Public Health and Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center, Columbia University, New York City, New York, USA
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Montes YD, Vergara TA, Molina RT, Guerrero GM, Arrieta LAA, Aschner P, Acosta-Reyes J, Florez-Garcia V, Lechuga EN, Barengo NC. The association between sociodemographic characteristics, clinical indicators and body mass index in a population at risk of type 2 diabetes: A cross-sectional study in two Colombian cities. Prim Care Diabetes 2024; 18:458-465. [PMID: 38862312 DOI: 10.1016/j.pcd.2024.06.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Revised: 05/25/2024] [Accepted: 06/02/2024] [Indexed: 06/13/2024]
Abstract
AIMS To assess the association between sociodemographic and clinical factors with body mass index (BMI) in a population at risk of type 2 diabetes (T2D) in Bogotá and Barranquilla, Colombia. METHODS This cross-sectional study used data from the PREDICOL Study. Participants with a FINDRISC ≥ 12 who underwent an Oral Glucose Tolerance Test (OGTT) were included in the study (n=1166). The final analytical sample size was 1101 participants. Those with missing data were excluded from the analysis (n=65). The main outcome was body mass index (BMI), which was categorized as normal, overweight, and obese. We utilized unadjusted and adjusted ordinal logistic regression analysis to calculate odds ratios (OR) and 95 % confidence intervals (CI). RESULTS The prevalence of overweight and obesity was 41 % (n=449) and 47 % (n=517), respectively. Participants with a 2-hour glucose ≥139 mg/dl had 1.71 times higher odds of being overweight or obese (regarding normal weight) than participants with normal 2-hour glucose values. In addition, being a woman, waist circumference altered, and blood pressure >120/80 mmHg were statistically significantly associated with a higher BMI. CONCLUSION Strategies to control glycemia, blood pressure, and central adiposity are needed in people at risk of T2D. Future studies should be considered with a territorial and gender focus, considering behavioral, and sociocultural patterns.
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Affiliation(s)
- Yenifer Diaz Montes
- Department of Preventive Medicine and Public Health. School of Medicine, Universidad Autónoma de Madrid, 28029 Madrid, Spain; Department of Public Health, Division of Health Sciences, Universidad del Norte, Km 5 vía Puerto Colombia, Barranquilla, Colombia; Faculty of Nursing Sciences, Universidad Cooperativa de Colombia, Santa Marta, Colombia.
| | - Tania Acosta Vergara
- Department of Public Health, Division of Health Sciences, Universidad del Norte, Km 5 vía Puerto Colombia, Barranquilla, Colombia
| | - Rafael Tuesca Molina
- Department of Public Health, Division of Health Sciences, Universidad del Norte, Km 5 vía Puerto Colombia, Barranquilla, Colombia; ScienceFlows Research Group, Universidad de Valencia, Valencia, Spain
| | - Gillian Martinez Guerrero
- Department of Public Health, Division of Health Sciences, Universidad del Norte, Km 5 vía Puerto Colombia, Barranquilla, Colombia
| | - Luis A Anillo Arrieta
- Department of Public Health, Division of Health Sciences, Universidad del Norte, Km 5 vía Puerto Colombia, Barranquilla, Colombia; College of Basic Sciences, Department of Mathematics and Statistics, Universidad del Norte, Barranquilla, Colombia
| | - Pablo Aschner
- Colombian Association for Diabetes, Bogotá, Colombia; Universidad Javeriana, Bogotá, Colombia; San Ignacio University Hospital, Bogotá, Colombia
| | - Jorge Acosta-Reyes
- Department of Preventive Medicine and Public Health. School of Medicine, Universidad Autónoma de Madrid, 28029 Madrid, Spain; Department of Public Health, Division of Health Sciences, Universidad del Norte, Km 5 vía Puerto Colombia, Barranquilla, Colombia
| | - Victor Florez-Garcia
- Department of Public Health, Division of Health Sciences, Universidad del Norte, Km 5 vía Puerto Colombia, Barranquilla, Colombia; Joseph J. Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI 53211, USA
| | - Edgar Navarro Lechuga
- Department of Public Health, Division of Health Sciences, Universidad del Norte, Km 5 vía Puerto Colombia, Barranquilla, Colombia
| | - Noël C Barengo
- Department of Medical Education, Herbert Wertheim College of Medicine, Florida International University, Miami, FL, USA; Escuela Superior de Medicina, Universidad Nacional de Mar del Plata, Mar del Plata, Argentina
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Kojima N, Koido M, He Y, Shimmori Y, Hachiya T, Japan B, Debette S, Kamatani Y. Recurrent stroke prediction by applying a stroke polygenic risk score in the Japanese population. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.06.17.24309034. [PMID: 39371120 PMCID: PMC11451717 DOI: 10.1101/2024.06.17.24309034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/08/2024]
Abstract
Background Recently, various polygenic risk score (PRS)-based methods were developed to improve stroke prediction. However, current PRSs (including cross-ancestry PRS) poorly predict recurrent stroke. Here, we aimed to determine whether the best PRS for Japanese individuals can also predict stroke recurrence in this population by extensively comparing the methods and maximizing the predictive performance for stroke onset. Methods We used data from the BioBank Japan (BBJ) 1st cohort (n=179,938) to derive and optimize the PRSs using a 10-fold cross-validation. We integrated the optimized PRSs for multiple traits, such as vascular risk factors and stroke subtypes to generate a single PRS using the meta-scoring approach (metaGRS). We used an independent BBJ 2nd cohort (n=41,929) as a test sample to evaluate the association of the metaGRS with stroke and recurrent stroke. Results We analyzed recurrent stroke cases (n=174) and non-recurrent stroke controls (n=1,153) among subjects within the BBJ 2nd cohort. After adjusting for known risk factors, metaGRS was associated with stroke recurrence (adjusted OR per SD 1.18 [95% CI: 1.00-1.39, p=0.044]), although no significant correlation was observed with the published PRSs. We administered three distinct tests to consider the potential index event bias; however, the outcomes derived from these examinations did not provide any significant indication of the influence of index event bias. The high metaGRS group without a history of hypertension had a higher risk of stroke recurrence than that of the low metaGRS group (adjusted OR 2.24 [95% CI: 1.07-4.66, p=0.032]). However, this association was weak in the hypertension group (adjusted OR 1.21 [95% CI: 0.69-2.13, p=0.50]). Conclusions The metaGRS developed in a Japanese cohort predicted stroke recurrence in an independent cohort of patients. In particular, it predicted an increased risk of recurrence among stroke patients without hypertension. These findings provide clues for additional genetic risk stratification and help in developing personalized strategies for stroke recurrence prevention.
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Affiliation(s)
- Naoki Kojima
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Masaru Koido
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yunye He
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yuka Shimmori
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Tsuyoshi Hachiya
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | | | - Stéphanie Debette
- Bordeaux Population Health Research Center, University of Bordeaux, Inserm, UMR 1219, Bordeaux, France
- Department of Neurology, Institute for Neurodegenerative Diseases, CHU de Bordeaux, Bordeaux, France
| | - Yoichiro Kamatani
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
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D’Esposito F, Gagliano C, Bloom PA, Cordeiro MF, Avitabile A, Gagliano G, Costagliola C, Avitabile T, Musa M, Zeppieri M. Epigenetics in Glaucoma. MEDICINA (KAUNAS, LITHUANIA) 2024; 60:905. [PMID: 38929522 PMCID: PMC11205742 DOI: 10.3390/medicina60060905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2024] [Revised: 05/17/2024] [Accepted: 05/28/2024] [Indexed: 06/28/2024]
Abstract
Primary open angle glaucoma (POAG) is defined as a "genetically complex trait", where modifying factors act on a genetic predisposing background. For the majority of glaucomatous conditions, DNA variants are not sufficient to explain pathogenesis. Some genes are clearly underlying the more "Mendelian" forms, while a growing number of related polymorphisms in other genes have been identified in recent years. Environmental, dietary, or biological factors are known to influence the development of the condition, but interactions between these factors and the genetic background are poorly understood. Several studies conducted in recent years have led to evidence that epigenetics, that is, changes in the pattern of gene expression without any changes in the DNA sequence, appear to be the missing link. Different epigenetic mechanisms have been proven to lead to glaucomatous changes in the eye, principally DNA methylation, post-translational histone modification, and RNA-associated gene regulation by non-coding RNAs. The aim of this work is to define the principal epigenetic actors in glaucoma pathogenesis. The identification of such mechanisms could potentially lead to new perspectives on therapeutic strategies.
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Affiliation(s)
- Fabiana D’Esposito
- Imperial College Ophthalmic Research Group (ICORG) Unit, Imperial College, London NW1 5QH, UK; (F.D.)
- Eye Clinic, Department of Neurosciences, Reproductive Sciences and Dentistry, University of Naples Federico II, 80131 Naples, Italy
- Department of Medicine and Surgery, University of Enna “Kore”, Piazza dell’Università, 94100 Enna, Italy
| | - Caterina Gagliano
- Department of Medicine and Surgery, University of Enna “Kore”, Piazza dell’Università, 94100 Enna, Italy
- Eye Clinic, Catania University San Marco Hospital, Viale Carlo Azeglio Ciampi, 95121 Catania, Italy
| | - Philip Anthony Bloom
- Imperial College Ophthalmic Research Group (ICORG) Unit, Imperial College, London NW1 5QH, UK; (F.D.)
- Western Eye Hospital, Imperial College Healthcare NHS Trust, London NW1 5QH, UK
| | - Maria Francesca Cordeiro
- Eye Clinic, Department of Neurosciences, Reproductive Sciences and Dentistry, University of Naples Federico II, 80131 Naples, Italy
- Western Eye Hospital, Imperial College Healthcare NHS Trust, London NW1 5QH, UK
| | - Alessandro Avitabile
- Eye Clinic, Catania University San Marco Hospital, Viale Carlo Azeglio Ciampi, 95121 Catania, Italy
| | - Giuseppe Gagliano
- Eye Clinic, Catania University San Marco Hospital, Viale Carlo Azeglio Ciampi, 95121 Catania, Italy
| | - Ciro Costagliola
- Eye Clinic, Department of Neurosciences, Reproductive Sciences and Dentistry, University of Naples Federico II, 80131 Naples, Italy
| | - Teresio Avitabile
- Eye Clinic, Catania University San Marco Hospital, Viale Carlo Azeglio Ciampi, 95121 Catania, Italy
| | - Mutali Musa
- Department of Optometry, University of Benin, Benin City 300238, Nigeria
| | - Marco Zeppieri
- Department of Ophthalmology, University Hospital of Udine, 33100 Udine, Italy
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Ter Hark SE, Coenen MJH, Vos CF, Aarnoutse RE, Nolen WA, Birkenhager TK, van den Broek WW, Schellekens AFA, Verkes RJ, Janzing JGE. A genetic risk score to predict treatment nonresponse in psychotic depression. Transl Psychiatry 2024; 14:132. [PMID: 38431658 PMCID: PMC10908776 DOI: 10.1038/s41398-024-02842-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 02/09/2024] [Accepted: 02/19/2024] [Indexed: 03/05/2024] Open
Abstract
Psychotic depression is a severe and difficult-to-treat subtype of major depressive disorder for which higher rates of treatment-resistant depression were found. Studies have been performed aiming to predict treatment-resistant depression or treatment nonresponse. However, most of these studies excluded patients with psychotic depression. We created a genetic risk score (GRS) based on a large treatment-resistant depression genome-wide association study. We tested whether this GRS was associated with nonresponse, nonremission and the number of prior adequate antidepressant trials in patients with a psychotic depression. Using data from a randomized clinical trial with patients with a psychotic depression (n = 122), we created GRS deciles and calculated positive prediction values (PPV), negative predictive values (NPV) and odds ratios (OR). Nonresponse and nonremission were assessed after 7 weeks of treatment with venlafaxine, imipramine or venlafaxine plus quetiapine. The GRS was negatively correlated with treatment response (r = -0.32, p = 0.0023, n = 88) and remission (r = -0.31, p = 0.0037, n = 88), but was not correlated with the number of prior adequate antidepressant trials. For patients with a GRS in the top 10%, we observed a PPV of 100%, a NPV of 73.7% and an OR of 52.4 (p = 0.00072, n = 88) for nonresponse. For nonremission, a PPV of 100%, a NPV of 51.9% and an OR of 21.3 (p = 0.036, n = 88) was observed for patients with a GRS in the top 10%. Overall, an increased risk for nonresponse and nonremission was seen in patients with GRSs in the top 40%. Our results suggest that a treatment-resistant depression GRS is predictive of treatment nonresponse and nonremission in psychotic depression.
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Affiliation(s)
- Sophie E Ter Hark
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands.
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands.
| | - Marieke J H Coenen
- Department of Clinical Chemistry, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Cornelis F Vos
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Rob E Aarnoutse
- Department of Pharmacy, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Willem A Nolen
- Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Tom K Birkenhager
- Department of Psychiatry, Erasmus University Medical Centre, Rotterdam, The Netherlands
| | | | - Arnt F A Schellekens
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
- Nijmegen Institute for Scientist Practitioners in Addiction (NISPA), Radboud University, Nijmegen, The Netherlands
| | - Robbert-Jan Verkes
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Joost G E Janzing
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
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Hubacek JA, Adamkova V, Lanska V, Staněk V, Mrázková J, Gebauerová M, Kettner J, Kautzner J, Pitha J. Cholesterol associated genetic risk score and acute coronary syndrome in Czech males. Mol Biol Rep 2024; 51:164. [PMID: 38252350 PMCID: PMC10803395 DOI: 10.1007/s11033-023-09128-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 12/07/2023] [Indexed: 01/23/2024]
Abstract
BACKGROUND Despite a general decline in mean levels across populations, LDL-cholesterol levels remain a major risk factor for acute coronary syndrome (ACS). The APOB, LDL-R, CILP, and SORT-1 genes have been shown to contain variants that have significant effects on plasma cholesterol levels. METHODS AND RESULTS We examined polymorphisms within these genes in 1191 controls and 929 patients with ACS. Only rs646776 within SORT-1 was significantly associated with a risk of ACS (P < 0.05, AA vs. + G comparison; OR 1.21; 95% CI 1.01-1.45). With regard to genetic risk score (GRS), the presence of at least 7 alleles associated with elevated cholesterol levels was connected with increased risk (P < 0.01) of ACS (OR 1.26; 95% CI 1.06-1.52). Neither total mortality nor CVD mortality in ACS subjects (follow up-9.84 ± 3.82 years) was associated with the SNPs analysed or cholesterol-associated GRS. CONCLUSIONS We conclude that, based on only a few potent SNPs known to affect plasma cholesterol, GRS has the potential to predict ACS risk, but not ACS associated mortality.
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Affiliation(s)
- Jaroslav A Hubacek
- Experimental Medicine Centre, Institute for Clinical and Experimental Medicine, IKEM-CEM-LMG, Videnska 1958/9, 140 21, Prague 4, Czech Republic.
- 3rd Department of Internal Medicine, 1st Faculty of Medicine, Charles University, Prague, Czech Republic.
| | - Vera Adamkova
- Preventive Cardiology Centre, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Vera Lanska
- Information Technology Division, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Vladimir Staněk
- Cardiac Centre, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Jolana Mrázková
- Experimental Medicine Centre, Institute for Clinical and Experimental Medicine, IKEM-CEM-LMG, Videnska 1958/9, 140 21, Prague 4, Czech Republic
| | - Marie Gebauerová
- Cardiac Centre, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Jiri Kettner
- Cardiac Centre, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Josef Kautzner
- Cardiac Centre, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Jan Pitha
- Experimental Medicine Centre, Institute for Clinical and Experimental Medicine, IKEM-CEM-LMG, Videnska 1958/9, 140 21, Prague 4, Czech Republic
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Osterman MD, Song YE, Lynn A, Miskimen K, Adams LD, Laux RA, Caywood LJ, Prough MB, Clouse JE, Herington SD, Slifer SH, Fuzzell SL, Hochstetler SD, Main LR, Dorfsman DA, Zaman AF, Ogrocki P, Lerner AJ, Vance JM, Cuccaro ML, Scott WK, Pericak-Vance MA, Haines JL. Founder population-specific weights yield improvements in performance of polygenic risk scores for Alzheimer disease in the Midwestern Amish. HGG ADVANCES 2023; 4:100241. [PMID: 37742071 PMCID: PMC10565871 DOI: 10.1016/j.xhgg.2023.100241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 09/16/2023] [Accepted: 09/16/2023] [Indexed: 09/25/2023] Open
Abstract
Alzheimer disease (AD) is the most common type of dementia and is estimated to affect 6 million Americans. Risk for AD is multifactorial, including both genetic and environmental risk factors. AD genomic research has generally focused on identification of risk variants. Using this information, polygenic risk scores (PRSs) can be calculated to quantify an individual's relative disease risk due to genetic factors. The Amish are a founder population descended from German and Swiss Anabaptist immigrants. They experienced a genetic bottleneck after arrival in the United States, making their genetic architecture different from the broader European ancestry population. Prior work has demonstrated the lack of transferability of PRSs across populations. Here, we compared the performance of PRSs derived from genome-wide association studies (GWASs) of Amish individuals to those derived from a large European ancestry GWAS. Participants were screened for cognitive impairment with further evaluation for AD. Genotype data were imputed after collection via Illumina genotyping arrays. The Amish individuals were split into two groups based on the primary site of recruitment. For each group, GWAS was conducted with account for relatedness and adjustment for covariates. PRSs were then calculated using weights from the other Amish group. PRS models were evaluated with and without covariates. The Amish-derived PRSs distinguished between dementia status better than the European-derived PRS in our Amish populations and demonstrated performance improvements despite a smaller training sample size. This work highlighted considerations for AD PRS usage in populations that cannot be adequately described by basic race/ethnicity or ancestry classifications.
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Affiliation(s)
- Michael D Osterman
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA; Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA.
| | - Yeunjoo E Song
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA; Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA
| | - Audrey Lynn
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA; Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA
| | - Kristy Miskimen
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Larry D Adams
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Renee A Laux
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Laura J Caywood
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Michael B Prough
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Jason E Clouse
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Sharlene D Herington
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Susan H Slifer
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Sarada L Fuzzell
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Sherri D Hochstetler
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Leighanne R Main
- Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA; Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Daniel A Dorfsman
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA; The Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Andrew F Zaman
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Paula Ogrocki
- Department of Neurology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA; Department of Neurology, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Alan J Lerner
- Department of Neurology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA; Department of Neurology, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Jeffery M Vance
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA; The Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Michael L Cuccaro
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA; The Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - William K Scott
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA; The Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Margaret A Pericak-Vance
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA; The Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Jonathan L Haines
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA; Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA.
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8
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Singh RK, Zhao Y, Elze T, Fingert J, Gordon M, Kass MA, Luo Y, Pasquale LR, Scheetz T, Segrè AV, Wiggs JL, Zebardast N. Polygenic Risk Score Improves Prediction of Primary Open Angle Glaucoma Onset in the Ocular Hypertension Treatment Study. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.08.15.23294141. [PMID: 37645858 PMCID: PMC10462203 DOI: 10.1101/2023.08.15.23294141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
Objective or Purpose Primary open-angle glaucoma (POAG) is a highly heritable disease with 127 identified risk loci. Polygenic risks score (PRS) offers a measure of aggregate genetic burden. In this study, we assess whether PRS improves risk stratification in patients with ocular hypertension. Design A post-hoc analysis of the Ocular Hypertension Treatment Study (OHTS) data. Setting Participants and/or Controls 1636 participants were followed from 1994 to 2020 across 22 sites. The PRS was computed for 1009 OHTS participants using summary statistics from largest cross-ancestry POAG metanalysis with weights trained using 8,813,496 variants from 488,395 participants in the UK Biobank. Methods Interventions or Testing Survival regression analysis, with endpoint as development of POAG, predicted disease onset from PRS incorporating baseline covariates. Main Outcomes and Measures Outcome measures were hazard ratios for POAG onset. Concordance index and time-dependent AUC were used to compare the predictive performance of multivariable Cox-Proportional Hazards models. Results Mean PRS was significantly higher for POAG-converters (0.24 ± 0.95) than for non-converters (-0.12 ± 1.00) (p < 0.01). POAG risk increased 1.36% with each higher PRS decile, with conversion ranging from 9.5% in the lowest PRS decile to 21.8% in the highest decile. Comparison of low- and high-risk PRS tertiles showed a 1.8-fold increase in 20-year POAG risk for participants of European and African ancestries (p<0.01). In the subgroup randomized to delayed treatment, each increase in PRS decile was associated with a 0.52-year decrease in age at diagnosis, (p=0.05). No significant linear relationship between PRS and age at POAG diagnosis was present in the early treatment group. Prediction models significantly improved with the addition of PRS as a covariate (C-index = 0.77) compared to OHTS baseline model (C-index=0.75) (p<0.01). One standard deviation higher PRS conferred a mean hazard ratio of 1.25 (CI=[1.13, 1.44]) for POAG onset. Conclusions Higher PRS is associated with increased risk for, and earlier development of POAG in patients with ocular hypertension. Early treatment may mitigate the risk from high genetic burden, delaying clinically detectable disease by up to 5.2 years. The inclusion of a PRS improves the prediction of POAG onset.
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Affiliation(s)
- Rishabh K. Singh
- Department of Ophthalmology, Columbia University Medical Center, New York, NY
- Schepens Eye Research Institute, Harvard Medical School, Boston, MA
| | - Yan Zhao
- Massachusetts Eye and Ear, Harvard Medical School, Boston, MA
| | - Tobias Elze
- Schepens Eye Research Institute, Harvard Medical School, Boston, MA
| | - John Fingert
- Carver College of Medicine, University of Iowa, Iowa City, IA
| | - Mae Gordon
- Washington University School of Medicine, St. Louis, MO
| | | | - Yuyang Luo
- Massachusetts Eye and Ear, Harvard Medical School, Boston, MA
| | | | - Todd Scheetz
- Carver College of Medicine, University of Iowa, Iowa City, IA
| | - Ayellet V. Segrè
- Massachusetts Eye and Ear, Harvard Medical School, Boston, MA
- Ocular Genomics Institute, Massachusetts Eye and Ear, Boston, MA
| | - Janey L. Wiggs
- Massachusetts Eye and Ear, Harvard Medical School, Boston, MA
- Ocular Genomics Institute, Massachusetts Eye and Ear, Boston, MA
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9
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Drouet DE, Liu S, Crawford DC. Assessment of multi-population polygenic risk scores for lipid traits in African Americans. PeerJ 2023; 11:e14910. [PMID: 37214096 PMCID: PMC10198155 DOI: 10.7717/peerj.14910] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Accepted: 01/25/2023] [Indexed: 05/24/2023] Open
Abstract
Polygenic risk scores (PRS) based on genome-wide discoveries are promising predictors or classifiers of disease development, severity, and/or progression for common clinical outcomes. A major limitation of most risk scores is the paucity of genome-wide discoveries in diverse populations, prompting an emphasis to generate these needed data for trans-population and population-specific PRS construction. Given diverse genome-wide discoveries are just now being completed, there has been little opportunity for PRS to be evaluated in diverse populations independent from the discovery efforts. To fill this gap, we leverage here summary data from a recent genome-wide discovery study of lipid traits (HDL-C, LDL-C, triglycerides, and total cholesterol) conducted in diverse populations represented by African Americans, Hispanics, Asians, Native Hawaiians, Native Americans, and others by the Population Architecture using Genomics and Epidemiology (PAGE) Study. We constructed lipid trait PRS using PAGE Study published genetic variants and weights in an independent African American adult patient population linked to de-identified electronic health records and genotypes from the Illumina Metabochip (n = 3,254). Using multi-population lipid trait PRS, we assessed levels of association for their respective lipid traits, clinical outcomes (cardiovascular disease and type 2 diabetes), and common clinical labs. While none of the multi-population PRS were strongly associated with the tested trait or outcome, PRSLDL-Cwas nominally associated with cardiovascular disease. These data demonstrate the complexity in applying PRS to real-world clinical data even when data from multiple populations are available.
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Affiliation(s)
- Domenica E. Drouet
- Department of Medicine, Case Western Reserve University, Cleveland, OH, United States of America
| | - Shiying Liu
- Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, United States of America
| | - Dana C. Crawford
- Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, United States of America
- Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, United States of America
- Genetics and Genome Sciences, Case Western Reserve University, Cleveland, OH, United States of America
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10
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Cooke Bailey JN, Funk KL, Cruz LA, Waksmunski AR, Kinzy TG, Wiggs JL, Hauser MA. Diversity in Polygenic Risk of Primary Open-Angle Glaucoma. Genes (Basel) 2022; 14:111. [PMID: 36672852 PMCID: PMC9859496 DOI: 10.3390/genes14010111] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 12/22/2022] [Accepted: 12/29/2022] [Indexed: 12/31/2022] Open
Abstract
Glaucoma is the leading cause of irreversible blindness worldwide. Primary open-angle glaucoma (POAG), the most common glaucoma subtype, is more prevalent and severe in individuals of African ancestry. Unfortunately, this ancestral group has been historically under-represented among genetic studies of POAG. Moreover, both genetic and polygenic risk scores (GRS, PRS) that are typically based on genetic data from European-descent populations are not transferable to individuals without a majority of European ancestry. Given the aspirations of leveraging genetic information for precision medicine, GRS and PRS demonstrate clinical potential but fall short, in part due to the lack of diversity in these studies. Prioritizing diversity in the discovery of risk variants will improve the performance and utility of GRS and PRS-derived risk estimation for disease stratification, which could bring about earlier POAG intervention and treatment for a disease that often goes undetected until significant damage has occurred.
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Affiliation(s)
- Jessica N. Cooke Bailey
- Cleveland Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
| | - Kaitlyn L. Funk
- Cleveland Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
| | - Lauren A. Cruz
- Cleveland Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
| | - Andrea R. Waksmunski
- Cleveland Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
| | - Tyler G. Kinzy
- Cleveland Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
| | - Janey L. Wiggs
- Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, MA 02115, USA
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11
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Waksmunski AR, Kinzy TG, Cruz LA, Nealon CL, Halladay CW, Simpson P, Canania RL, Anthony SA, Roncone DP, Sawicki Rogers L, Leber JN, Dougherty JM, Greenberg PB, Sullivan JM, Wu WC, Iyengar SK, Crawford DC, Peachey NS, Cooke Bailey JN. Glaucoma Genetic Risk Scores in the Million Veteran Program. Ophthalmology 2022; 129:1263-1274. [PMID: 35718050 PMCID: PMC9997524 DOI: 10.1016/j.ophtha.2022.06.012] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Revised: 06/07/2022] [Accepted: 06/09/2022] [Indexed: 11/22/2022] Open
Abstract
PURPOSE Primary open-angle glaucoma (POAG) is a degenerative eye disease for which early treatment is critical to mitigate visual impairment and irreversible blindness. POAG-associated loci individually confer incremental risk. Genetic risk score(s) (GRS) could enable POAG risk stratification. Despite significantly higher POAG burden among individuals of African ancestry (AFR), GRS are limited in this population. A recent large-scale, multi-ancestry meta-analysis identified 127 POAG-associated loci and calculated cross-ancestry and ancestry-specific effect estimates, including in European ancestry (EUR) and AFR individuals. We assessed the utility of the 127-variant GRS for POAG risk stratification in EUR and AFR Veterans in the Million Veteran Program (MVP). We also explored the association between GRS and documented invasive glaucoma surgery (IGS). DESIGN Cross-sectional study. PARTICIPANTS MVP Veterans with imputed genetic data, including 5830 POAG cases (445 with IGS documented in the electronic health record) and 64 476 controls. METHODS We tested unweighted and weighted GRS of 127 published risk variants in EUR (3382 cases and 58 811 controls) and AFR (2448 cases and 5665 controls) Veterans in the MVP. Weighted GRS were calculated using effect estimates from the most recently published report of cross-ancestry and ancestry-specific meta-analyses. We also evaluated GRS in POAG cases with documented IGS. MAIN OUTCOME MEASURES Performance of 127-variant GRS in EUR and AFR Veterans for POAG risk stratification and association with documented IGS. RESULTS GRS were significantly associated with POAG (P < 5 × 10-5) in both groups; a higher proportion of EUR compared with AFR were consistently categorized in the top GRS decile (21.9%-23.6% and 12.9%-14.5%, respectively). Only GRS weighted by ancestry-specific effect estimates were associated with IGS documentation in AFR cases; all GRS types were associated with IGS in EUR cases. CONCLUSIONS Varied performance of the GRS for POAG risk stratification and documented IGS association in EUR and AFR Veterans highlights (1) the complex risk architecture of POAG, (2) the importance of diverse representation in genomics studies that inform GRS construction and evaluation, and (3) the necessity of expanding diverse POAG-related genomic data so that GRS can equitably aid in screening individuals at high risk of POAG and who may require more aggressive treatment.
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Affiliation(s)
- Andrea R Waksmunski
- Cleveland Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, Ohio; Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio
| | - Tyler G Kinzy
- Cleveland Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, Ohio; Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio; Research Service, VA Northeast Ohio Healthcare System, Cleveland, Ohio
| | - Lauren A Cruz
- Cleveland Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, Ohio; Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio
| | - Cari L Nealon
- Eye Clinic, VA Northeast Ohio Healthcare System, Cleveland, Ohio
| | - Christopher W Halladay
- Center of Innovation in Long Term Services and Supports, Providence VA Medical Center, Providence, Rhode Island
| | - Piana Simpson
- Eye Clinic, VA Northeast Ohio Healthcare System, Cleveland, Ohio
| | | | - Scott A Anthony
- Eye Clinic, VA Northeast Ohio Healthcare System, Cleveland, Ohio
| | - David P Roncone
- Eye Clinic, VA Northeast Ohio Healthcare System, Cleveland, Ohio
| | - Lea Sawicki Rogers
- Ophthalmology Section, VA Western NY Healthcare System, Buffalo, New York
| | - Jenna N Leber
- Ophthalmology Section, VA Western NY Healthcare System, Buffalo, New York
| | | | - Paul B Greenberg
- Ophthalmology Section, Providence VA Medical Center, Providence, Rhode Island; Division of Ophthalmology, Alpert Medical School, Brown University, Providence, Rhode Island
| | - Jack M Sullivan
- Ophthalmology Section, VA Western NY Healthcare System, Buffalo, New York; Research Service, VA Western NY Healthcare System, Buffalo, New York
| | - Wen-Chih Wu
- Cardiology Section, Medical Service, Providence VA Medical Center, Providence, Rhode Island
| | - Sudha K Iyengar
- Cleveland Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, Ohio; Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio; Research Service, VA Northeast Ohio Healthcare System, Cleveland, Ohio
| | - Dana C Crawford
- Cleveland Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, Ohio; Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio; Research Service, VA Northeast Ohio Healthcare System, Cleveland, Ohio
| | - Neal S Peachey
- Research Service, VA Northeast Ohio Healthcare System, Cleveland, Ohio; Cole Eye Institute, Cleveland Clinic Foundation, Cleveland, Ohio; Department of Ophthalmology, Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, Ohio
| | - Jessica N Cooke Bailey
- Cleveland Institute for Computational Biology, Case Western Reserve University School of Medicine, Cleveland, Ohio; Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio; Research Service, VA Northeast Ohio Healthcare System, Cleveland, Ohio.
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12
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Osterman MD, Song YE, Adams LD, Laux RA, Caywood LJ, Prough MB, Clouse JE, Herington SD, Slifer SH, Lynn A, Fuzzell MD, Fuzzell SL, Hochstetler SD, Miskimen K, Main LR, Dorfsman DA, Ogrocki P, Lerner AJ, Ramos J, Vance JM, Cuccaro ML, Scott WK, Pericak-Vance MA, Haines JL. The genetic architecture of Alzheimer disease risk in the Ohio and Indiana Amish. HGG ADVANCES 2022; 3:100114. [PMID: 35599847 PMCID: PMC9114685 DOI: 10.1016/j.xhgg.2022.100114] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 04/22/2022] [Indexed: 11/26/2022] Open
Abstract
Alzheimer disease (AD) is the most common type of dementia and is currently estimated to affect 6.2 million Americans. It ranks as the sixth leading cause of death in the United States, and the proportion of deaths due to AD has been increasing since 2000, while the proportion of many other leading causes of deaths have decreased or remained constant. The risk for AD is multifactorial, including genetic and environmental risk factors. Although APOE ε4 remains the largest genetic risk factor for AD, more than 26 other loci have been associated with AD risk. Here, we recruited Amish adults from Ohio and Indiana to investigate AD risk and protective genetic effects. As a founder population that typically practices endogamy, variants that are rare in the general population may be of a higher frequency in the Amish population. Since the Amish have a slightly lower incidence and later age of onset of disease, they represent an excellent and unique population for research on protective genetic variants. We compared AD risk in the Amish and to a non-Amish population through APOE genotype, a non-APOE genetic risk score of genome-wide significant variants, and a non-APOE polygenic risk score considering all of the variants. Our results highlight the lesser relative impact of APOE and differing genetic architecture of AD risk in the Amish compared to a non-Amish, general European ancestry population.
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Affiliation(s)
- Michael D. Osterman
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA
- Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA
| | - Yeunjoo E. Song
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Larry D. Adams
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Renee A. Laux
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Laura J. Caywood
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Michael B. Prough
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Jason E. Clouse
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Sharlene D. Herington
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Susan H. Slifer
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Audrey Lynn
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - M. Denise Fuzzell
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Sarada L. Fuzzell
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Sherri D. Hochstetler
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Kristy Miskimen
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Leighanne R. Main
- Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA
- Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Daniel A. Dorfsman
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Paula Ogrocki
- Department of Neurology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
- Department of Neurology, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Alan J. Lerner
- Department of Neurology, University Hospitals Cleveland Medical Center, Cleveland, OH, USA
- Department of Neurology, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Jairo Ramos
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Jeffery M. Vance
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Michael L. Cuccaro
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - William K. Scott
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Margaret A. Pericak-Vance
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Jonathan L. Haines
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA
- Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA
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