101
|
Xiao Z, Li Y, Yang L, Cui M, Wang Z, Sun W, Wang J, Chen S, Lai S, Jia X. Genome-Wide Association Studies of Growth Trait Heterosis in Crossbred Meat Rabbits. Animals (Basel) 2024; 14:2096. [PMID: 39061558 PMCID: PMC11273820 DOI: 10.3390/ani14142096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2024] [Revised: 07/07/2024] [Accepted: 07/12/2024] [Indexed: 07/28/2024] Open
Abstract
The application of heterosis can not only effectively improve the disease resistance and meat quality of livestock, but also significantly enhance the reproduction and growth of livestock and poultry. We conducted genome-wide association studies using data from F2 crossbred meat rabbits to screen out candidate genes with significant dominant effects associated with economic trait variation. High-throughput sequencing technology was used to obtain SNPs covering the whole genome to evaluate the homozygosity of the population genome, and analyze the number, length, frequency, and distribution of ROHs in the population. Candidate genes related to economic traits of meat rabbits were searched based on high-frequency ROH regions. After quality control filtering of genotype data, 380 F2 crossbred rabbits were identified with 78,579 SNPs and 42,018 ROHs on the autosomes. The fitting of the Logistic growth curve model showed that 49-day-old rabbits were a growth inflection point. Then, through genome-wide association studies, 10 SNP loci and seven growth trait candidate genes were found to be significantly related to body weight in meat rabbits at 84 days of age. In addition, we revealed the functional roles and locations of 20 candidate genes in the high-frequency ROH region associated with economic traits in meat rabbits. This study identified potential genes associated with growth and development in the high-frequency ROH region of meat rabbits. In this study, the identified candidate genes can be used as molecular markers for assisted selection in meat rabbits. At the same time, the inbreeding situation based on ROH assessment can provide reference for breeding and breeding preservation of meat rabbits.
Collapse
Affiliation(s)
- Zhanjun Xiao
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China; (Z.X.); (M.C.); (Z.W.); (W.S.); (S.C.); (S.L.)
| | - Yuchao Li
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 610000, China; (Y.L.); (L.Y.); (J.W.)
| | - Li Yang
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 610000, China; (Y.L.); (L.Y.); (J.W.)
| | - Mingyan Cui
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China; (Z.X.); (M.C.); (Z.W.); (W.S.); (S.C.); (S.L.)
| | - Zicheng Wang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China; (Z.X.); (M.C.); (Z.W.); (W.S.); (S.C.); (S.L.)
| | - Wenqiang Sun
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China; (Z.X.); (M.C.); (Z.W.); (W.S.); (S.C.); (S.L.)
| | - Jie Wang
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 610000, China; (Y.L.); (L.Y.); (J.W.)
| | - Shiyi Chen
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China; (Z.X.); (M.C.); (Z.W.); (W.S.); (S.C.); (S.L.)
| | - Songjia Lai
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China; (Z.X.); (M.C.); (Z.W.); (W.S.); (S.C.); (S.L.)
| | - Xianbo Jia
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China; (Z.X.); (M.C.); (Z.W.); (W.S.); (S.C.); (S.L.)
| |
Collapse
|
102
|
Mendes M, Chen DZ, Engchuan W, Leal TP, Thiruvahindrapuram B, Trost B, Howe JL, Pellecchia G, Nalpathamkalam T, Alexandrova R, Salazar NB, McKee EA, Alfaro NR, Lai MC, Bandres-Ciga S, Roshandel D, Bradley CA, Anagnostou E, Sun L, Scherer SW. Chromosome X-Wide Common Variant Association Study (XWAS) in Autism Spectrum Disorder. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.07.18.24310640. [PMID: 39108515 PMCID: PMC11302709 DOI: 10.1101/2024.07.18.24310640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 08/12/2024]
Abstract
Autism Spectrum Disorder (ASD) displays a notable male bias in prevalence. Research into rare (<0.1) genetic variants on the X chromosome has implicated over 20 genes in ASD pathogenesis, such as MECP2, DDX3X, and DMD. The "female protective effect" in ASD suggests that females may require a higher genetic burden to manifest similar symptoms as males, yet the mechanisms remain unclear. Despite technological advances in genomics, the complexity of the biological nature of sex chromosomes leave them underrepresented in genome-wide studies. Here, we conducted an X chromosome-wide association study (XWAS) using whole-genome sequencing data from 6,873 individuals with ASD (82% males) across Autism Speaks MSSNG, Simons Simplex Cohort SSC, and Simons Foundation Powering Autism Research SPARK, alongside 8,981 population controls (43% males). We analyzed 418,652 X-chromosome variants, identifying 59 associated with ASD (p-values 7.9×10-6 to 1.51×10-5), surpassing Bonferroni-corrected thresholds. Key findings include significant regions on chrXp22.2 (lead SNP=rs12687599, p=3.57×10-7) harboring ASB9/ASB11, and another encompassing DDX53/PTCHD1-AS long non-coding RNA (lead SNP=rs5926125, p=9.47×10-6). When mapping genes within 10kb of the 59 most significantly associated SNPs, 91 genes were found, 17 of which yielded association with ASD (GRPR, AP1S2, DDX53, HDAC8, PCDH19, PTCHD1, PCDH11X, PTCHD1-AS, DMD, SYAP1, CNKSR2, GLRA2, OFD1, CDKL5, GPRASP2, NXF5, SH3KBP1). FGF13 emerged as a novel X-linked ASD candidate gene, highlighted by sex-specific differences in minor allele frequencies. These results reveal significant new insights into X chromosome biology in ASD, confirming and nominating genes and pathways for further investigation.
Collapse
Affiliation(s)
- Marla Mendes
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
| | - Desmond Zeya Chen
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
- Department of Statistical Sciences, Faculty of Arts and Science, University of Toronto, Toronto, ON, M5G 1X6, Canada
| | - Worrawat Engchuan
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
| | - Thiago Peixoto Leal
- Lerner Research Institute, Genomic Medicine, Cleveland Clinic, Cleveland, OH, 44106, USA
| | - Bhooma Thiruvahindrapuram
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
| | - Brett Trost
- Molecular Medicine Program, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, M5S 1A8, Canada
| | - Jennifer L. Howe
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
| | - Giovanna Pellecchia
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
| | - Thomas Nalpathamkalam
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
| | - Roumiana Alexandrova
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
| | - Nelson Bautista Salazar
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
| | - Ethan Alexander McKee
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
| | - Natalia Rivera Alfaro
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
| | - Meng-Chuan Lai
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, M5G 2C1, Canada
- Department of Psychiatry, The Hospital for Sick Children, Toronto, ON, M5G 1E8, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, M5T 1R8, Canada
| | - Sara Bandres-Ciga
- Center for Alzheimer’s and Related Dementias, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Delnaz Roshandel
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
| | - Clarrisa A. Bradley
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
| | - Evdokia Anagnostou
- Autism Research Centre, Holland Bloorview Kids Rehabilitation Hospital, Toronto, ON, M4G 1R8, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, M5S 1A8, Canada
| | - Lei Sun
- Department of Statistical Sciences, Faculty of Arts and Science, University of Toronto, Toronto, ON, M5G 1X6, Canada
- Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, M5S 3E3, Canada
| | - Stephen W. Scherer
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, ON, M5G 0A4, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, M5S 1A8, Canada
- McLaughlin Centre and Department of Molecular Genetics, University of Toronto, Toronto, ON, M5S 1A8, Canada
| |
Collapse
|
103
|
Subramanian K, Chopra M, Kahali B. Landscape of genomic structural variations in Indian population-based cohorts: Deeper insights into their prevalence and clinical relevance. HGG ADVANCES 2024; 5:100285. [PMID: 38521976 PMCID: PMC11007539 DOI: 10.1016/j.xhgg.2024.100285] [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: 09/14/2023] [Revised: 03/13/2024] [Accepted: 03/20/2024] [Indexed: 03/25/2024] Open
Abstract
Structural variations (SV) are large (>50 base pairs) genomic rearrangements comprising deletions, duplications, insertions, inversions, and translocations. Studying SVs is important because they play active and critical roles in regulating gene expression, determining disease predispositions, and identifying population-specific differences among individuals of diverse ancestries. However, SV discoveries in the Indian population using whole-genome sequencing (WGS) have been limited. In this study, using short-read WGS having an average 42X depth of coverage, we identify and characterize 36,210 SVs from 529 individuals enrolled in population-based cohorts in India. These SVs include 24,574 deletions, 2,913 duplications, 8,710 insertions, and 13 inversions; 1.26% (456 out of 36,210) of the identified SVs can potentially impact the coding regions of genes. Furthermore, 56 of these SVs are highly intolerant to loss-of-function changes to the mapped genes, and five SVs impacting ADAMTS17, CCDC40, and RHCE are common in our study individuals. Seven rare SVs significantly impact dosage sensitivity of genes known to be associated with various clinical phenotypes. Most of the SVs in our study are rare and heterozygous. This fine-scale SV discovery in the underrepresented Indian population provides valuable insights that extend beyond Eurocentric human genetic studies.
Collapse
Affiliation(s)
- Krithika Subramanian
- Centre for Brain Research, Indian Institute of Science, Bangalore 560012, India; Manipal Academy of Higher Education, Manipal, Karnataka 576104, India
| | - Mehak Chopra
- Centre for Brain Research, Indian Institute of Science, Bangalore 560012, India
| | - Bratati Kahali
- Centre for Brain Research, Indian Institute of Science, Bangalore 560012, India.
| |
Collapse
|
104
|
Chen YC, Liaw YC, Nfor ON, Hsiao CH, Zhong JH, Wu SL, Liaw YP. Epigenetic associations of GPNMB rs199347 variant with alcohol consumption in Parkinson's disease. Front Psychiatry 2024; 15:1377403. [PMID: 39091454 PMCID: PMC11293056 DOI: 10.3389/fpsyt.2024.1377403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Accepted: 06/27/2024] [Indexed: 08/04/2024] Open
Abstract
Introduction Alcohol consumption can induce a neuroinflammatory response and contribute to the progression of neurodegeneration. However, its association with Parkinson's disease (PD), the second most common neurodegenerative disorder, remains undetermined. Recent studies suggest that the glycoprotein non-metastatic melanoma protein B (GPNMB) is a potential biomarker for PD. We evaluated the association of rs199347, a variant of the GPNMB gene, with alcohol consumption and methylation upstream of GPNMB. Methods We retrieved genetic and DNA methylation data obtained from participants enrolled in the Taiwan Biobank (TWB) between 2008 and 2016. After excluding individuals with incomplete or missing information about potential PD risk factors, we included 1,357 participants in our final analyses. We used multiple linear regression to assess the association of GPNMB rs199347 and chronic alcohol consumption (and other potential risk factors) with GPNMB cg17274742 methylation. Results There was no difference between the distribution of GPNMB rs199347 genotypes between chronic alcohol consumers and the other study participants. A significant interaction was observed between the GPNMB rs199347 variant and alcohol consumption (p = 0.0102) concerning cg17274742 methylation. Compared to non-chronic alcohol consumers with the AA genotype, alcohol drinkers with the rs199347 GG genotype had significantly lower levels (hypomethylation) of cg17274742 (p = 0.0187). Conclusion Alcohol consumption among individuals with the rs199347 GG genotype was associated with lower levels of cg17274742 methylation, which could increase expression of the GPNMB gene, an important neuroinflammatory-related risk gene for PD.
Collapse
Affiliation(s)
- Yen-Chung Chen
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, Taichung, Taiwan
- Department of Neurology, Changhua Christian Hospital, Changhua, Taiwan
| | - Yi-Chia Liaw
- Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Oswald Ndi Nfor
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, Taichung, Taiwan
| | - Chih-Hsuan Hsiao
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, Taichung, Taiwan
| | - Ji-Han Zhong
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, Taichung, Taiwan
| | - Shey-Lin Wu
- Department of Neurology, Changhua Christian Hospital, Changhua, Taiwan
- Department of Electrical Engineering, National Changhua University of Education, Changhua, Taiwan
| | - Yung-Po Liaw
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, Taichung, Taiwan
- Department of Medical Imaging, Chung Shan Medical University Hospital, Taichung, Taiwan
- Institute of Medicine, Chung Shan Medical University, Taichung, Taiwan
| |
Collapse
|
105
|
Biddanda A, Bandyopadhyay E, de la Fuente Castro C, Witonsky D, Urban Aragon JA, Pasupuleti N, Moots HM, Fonseca R, Freilich S, Stanisavic J, Willis T, Menon A, Mustak MS, Kodira CD, Naren AP, Sikdar M, Rai N, Raghavan M. Distinct positions of genetic and oral histories: Perspectives from India. HGG ADVANCES 2024; 5:100305. [PMID: 38720459 PMCID: PMC11153255 DOI: 10.1016/j.xhgg.2024.100305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 05/04/2024] [Accepted: 05/04/2024] [Indexed: 05/16/2024] Open
Abstract
Over the past decade, genomic data have contributed to several insights on global human population histories. These studies have been met both with interest and critically, particularly by populations with oral histories that are records of their past and often reference their origins. While several studies have reported concordance between oral and genetic histories, there is potential for tension that may stem from genetic histories being prioritized or used to confirm community-based knowledge and ethnography, especially if they differ. To investigate the interplay between oral and genetic histories, we focused on the southwestern region of India and analyzed whole-genome sequence data from 156 individuals identifying as Bunt, Kodava, Nair, and Kapla. We supplemented limited anthropological records on these populations with oral history accounts from community members and historical literature, focusing on references to non-local origins such as the ancient Scythians in the case of Bunt, Kodava, and Nair, members of Alexander the Great's army for the Kodava, and an African-related source for Kapla. We found these populations to be genetically most similar to other Indian populations, with the Kapla more similar to South Indian tribal populations that maximize a genetic ancestry related to Ancient Ancestral South Indians. We did not find evidence of additional genetic sources in the study populations than those known to have contributed to many other present-day South Asian populations. Our results demonstrate that oral and genetic histories may not always provide consistent accounts of population origins and motivate further community-engaged, multi-disciplinary investigations of non-local origin stories in these communities.
Collapse
Affiliation(s)
- Arjun Biddanda
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Esha Bandyopadhyay
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Constanza de la Fuente Castro
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA; Programa de Genética Humana, Instituto de Ciencias Biomédicas, Facultad de Medicina, Universidad de Chile, Santiago, Chile
| | - David Witonsky
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | | | - Nagarjuna Pasupuleti
- Department of Applied Zoology, Mangalore University, Mangalagangothri, Karnataka 574199, India
| | - Hannah M Moots
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA; Institute for the Study of Ancient Cultures Museum, University of Chicago, Chicago, IL, USA
| | - Renée Fonseca
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Suzanne Freilich
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA; Department of Evolutionary Anthropology, University of Vienna, Vienna 1090, Austria
| | - Jovan Stanisavic
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Tabitha Willis
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Anoushka Menon
- Department of Archaeology, University of Cambridge, Cambridge CB2 3DZ, UK
| | - Mohammed S Mustak
- Department of Applied Zoology, Mangalore University, Mangalagangothri, Karnataka 574199, India
| | | | - Anjaparavanda P Naren
- Division of Pulmonary Medicine, Cystic Fibrosis Research Center, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Mithun Sikdar
- Anthropological Survey of India, Mysore, Karnataka 570026, India
| | - Niraj Rai
- Birbal Sahni Institute of Palaeosciences, Uttar Pradesh, Lucknow, Uttar Pradesh 226007, India.
| | - Maanasa Raghavan
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA.
| |
Collapse
|
106
|
Lin Z, Pan W. A robust cis-Mendelian randomization method with application to drug target discovery. Nat Commun 2024; 15:6072. [PMID: 39025905 PMCID: PMC11258283 DOI: 10.1038/s41467-024-50385-y] [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: 08/04/2023] [Accepted: 07/08/2024] [Indexed: 07/20/2024] Open
Abstract
Mendelian randomization (MR) uses genetic variants as instrumental variables (IVs) to investigate causal relationships between traits. Unlike conventional MR, cis-MR focuses on a single genomic region using only cis-SNPs. For example, using cis-pQTLs for a protein as exposure for a disease opens a cost-effective path for drug target discovery. However, few methods effectively handle pleiotropy and linkage disequilibrium (LD) of cis-SNPs. Here, we propose cisMR-cML, a method based on constrained maximum likelihood, robust to IV assumption violations with strong theoretical support. We further clarify the severe but largely neglected consequences of the current practice of modeling marginal, instead of conditional genetic effects, and only using exposure-associated SNPs in cis-MR analysis. Numerical studies demonstrated our method's superiority over other existing methods. In a drug-target analysis for coronary artery disease (CAD), including a proteome-wide application, we identified three potential drug targets, PCSK9, COLEC11 and FGFR1 for CAD.
Collapse
Affiliation(s)
- Zhaotong Lin
- Division of Biostatistics and Health Data Science, University of Minnesota, Minneapolis, MN, 55455, USA.
- Department of Statistics, Florida State University, Tallahassee, FL, 32306, USA.
| | - Wei Pan
- Division of Biostatistics and Health Data Science, University of Minnesota, Minneapolis, MN, 55455, USA
| |
Collapse
|
107
|
Tkachenko AA, Changalidis AI, Maksiutenko EM, Nasykhova YA, Barbitoff YA, Glotov AS. Replication of Known and Identification of Novel Associations in Biobank-Scale Datasets: A Survey Using UK Biobank and FinnGen. Genes (Basel) 2024; 15:931. [PMID: 39062709 PMCID: PMC11275374 DOI: 10.3390/genes15070931] [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: 03/19/2024] [Revised: 07/03/2024] [Accepted: 07/07/2024] [Indexed: 07/28/2024] Open
Abstract
Over the last two decades, numerous genome-wide association studies (GWAS) have been performed to unveil the genetic architecture of human complex traits. Despite multiple efforts aimed at the trans-biobank integration of GWAS results, no systematic analysis of the variant-level properties affecting the replication of known associations (or identifying novel ones) in genome-wide meta-analysis has yet been performed using biobank-scale data. To address this issue, we performed a systematic comparison of GWAS summary statistics for 679 complex traits in the UK Biobank (UKB) and FinnGen (FG) cohorts. We identified 37,148 index variants with genome-wide associations with at least one trait in either cohort or in the meta-analysis, only 3528 (9.5%) of which were shared between UKB and FG. Nearly twice as many variants (6577) were replicated in another dataset at the significance level adjusted for the number of variants selected for replication. However, as many as 9230 loci failed to be replicated. Moreover, as many as 5813 loci were observed as significant associations only in meta-analysis results, highlighting the importance of trans-biobank meta-analysis efforts. We showed that variants that failed to replicate in UKB or FG tend to correspond to rare, less pleiotropic variants with lower effect sizes and lower LD score values. Genome-wide associations specific to meta-analysis were also enriched in low-effect variants; however, such variants tended to be more common and have more consistent frequencies between populations. Taken together, our results show a relatively high rate of non-replication of genome-wide associations in the studied cohorts and highlight both widely appreciated and less acknowledged properties of the associations affecting their identification and replication.
Collapse
Affiliation(s)
| | | | | | | | - Yury A. Barbitoff
- Department of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology, and Reproductology, 199034 St. Petersburg, Russia; (A.A.T.); (A.I.C.); (E.M.M.); (Y.A.N.); (A.S.G.)
| | | |
Collapse
|
108
|
Sonehara K, Yano Y, Naito T, Goto S, Yoshihara H, Otani T, Ozawa F, Kitaori T, Matsuda K, Nishiyama T, Okada Y, Sugiura-Ogasawara M. Common and rare genetic variants predisposing females to unexplained recurrent pregnancy loss. Nat Commun 2024; 15:5744. [PMID: 39019884 PMCID: PMC11255296 DOI: 10.1038/s41467-024-49993-5] [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: 11/21/2023] [Accepted: 06/25/2024] [Indexed: 07/19/2024] Open
Abstract
Recurrent pregnancy loss (RPL) is a major reproductive health issue with multifactorial causes, affecting 2.6% of all pregnancies worldwide. Nearly half of the RPL cases lack clinically identifiable causes (e.g., antiphospholipid syndrome, uterine anomalies, and parental chromosomal abnormalities), referred to as unexplained RPL (uRPL). Here, we perform a genome-wide association study focusing on uRPL in 1,728 cases and 24,315 female controls of Japanese ancestry. We detect significant associations in the major histocompatibility complex (MHC) region at 6p21 (lead variant=rs9263738; P = 1.4 × 10-10; odds ratio [OR] = 1.51 [95% CI: 1.33-1.72]; risk allele frequency = 0.871). The MHC associations are fine-mapped to the classical HLA alleles, HLA-C*12:02, HLA-B*52:01, and HLA-DRB1*15:02 (P = 1.1 × 10-10, 1.5 × 10-10, and 1.2 × 10-9, respectively), which constitute a population-specific common long-range haplotype with a protective effect (P = 2.8 × 10-10; OR = 0.65 [95% CI: 0.57-0.75]; haplotype frequency=0.108). Genome-wide copy-number variation (CNV) calling demonstrates rare predicted loss-of-function (pLoF) variants of the cadherin-11 gene (CDH11) conferring the risk of uRPL (P = 1.3 × 10-4; OR = 3.29 [95% CI: 1.78-5.76]). Our study highlights the importance of reproductive immunology and rare variants in the uRPL etiology.
Collapse
Affiliation(s)
- Kyuto Sonehara
- Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Suita, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yoshitaka Yano
- Department of Obstetrics and Gynecology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Tatsuhiko Naito
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Suita, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Shinobu Goto
- Department of Obstetrics and Gynecology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Hiroyuki Yoshihara
- Department of Obstetrics and Gynecology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Takahiro Otani
- Department of Public Health, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Fumiko Ozawa
- Department of Obstetrics and Gynecology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Tamao Kitaori
- Department of Obstetrics and Gynecology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Koichi Matsuda
- Laboratory of Genome Technology, Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo, Japan
- Laboratory of Clinical Genome Sequencing, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, the University of Tokyo, Tokyo, Japan
| | - Takashi Nishiyama
- Department of Public Health, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Yukinori Okada
- Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan.
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Suita, Japan.
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Osaka, Suita, Japan.
- Premium Research Institute for Human Metaverse Medicine (WPI-PRIMe), Osaka University, Osaka, Suita, Japan.
| | - Mayumi Sugiura-Ogasawara
- Department of Obstetrics and Gynecology, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan.
| |
Collapse
|
109
|
Cui Z, Schumacher FR. Small-group originating model: Optimized individual-level GWAS simulation featured by SLiM and using open-access data. Comput Biol Chem 2024; 112:108147. [PMID: 39033733 DOI: 10.1016/j.compbiolchem.2024.108147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Revised: 05/22/2024] [Accepted: 07/08/2024] [Indexed: 07/23/2024]
Abstract
The development of analytical methods for Genome-wide Association Studies (GWAS) has outpaced the evolution of simulation techniques and pipelines. This disparity underscores the importance of innovative simulation methods that can keep pace with the rapidly increasing scale of GWAS. The median sample size of GWAS over the past ten years has exceeded 50,000 individuals, a trend that emphasizes the need for simulation tools capable of generating data on a similar or larger scale. This paper introduces a novel method, the small-group originating (SGO) model, utilizing the SLiM software for simulating individual-level GWAS data. Our standardized protocol facilitates the generation of tens of thousands of pseudo-individuals with millions of variants from small (30-90) open-access datasets. SGO stands out, especially when compared to the widely-used resampling method in HapGen, showcasing superior simulation efficiency for large sample sizes (> 13,000) of unrelated individuals. This capability is particularly relevant given the current trajectory towards larger GWAS, necessitating tools that can simulate datasets reflective of this growth. Additionally, SGO provides customization options and can model dynamic life cycles and mating across generations, positioning it as a highly promising alternative for GWAS simulations. In a case study, sensitivity analyses of chromosome-level principal component analysis and kinship coefficient estimation were conducted. The results highlighted the poor robustness of chromosome-level quality control (QC) indexes and the uneven distribution of population structure across chromosomes and ancestries, advocating for the caution against relying solely on chromosome-level QC statistics. With its flexible and efficient approach to generating pseudo GWAS data, our standardized SGO protocol emerges as a crucial asset for method development, power analysis, and benchmarking in GWAS research. It is especially vital in the context of accommodating the demands for large-scale simulations, aligning with the current and future scale of GWAS.
Collapse
Affiliation(s)
- Zuxi Cui
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Fredrick R Schumacher
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH, USA; Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, OH, USA.
| |
Collapse
|
110
|
Yang L, Ou YN, Wu BS, Liu WS, Deng YT, He XY, Chen YL, Kang J, Fei CJ, Zhu Y, Tan L, Dong Q, Feng J, Cheng W, Yu JT. Large-scale whole-exome sequencing analyses identified protein-coding variants associated with immune-mediated diseases in 350,770 adults. Nat Commun 2024; 15:5924. [PMID: 39009607 PMCID: PMC11250857 DOI: 10.1038/s41467-024-49782-0] [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: 11/16/2023] [Accepted: 06/18/2024] [Indexed: 07/17/2024] Open
Abstract
The genetic contribution of protein-coding variants to immune-mediated diseases (IMDs) remains underexplored. Through whole exome sequencing of 40 IMDs in 350,770 UK Biobank participants, we identified 162 unique genes in 35 IMDs, among which 124 were novel genes. Several genes, including FLG which is associated with atopic dermatitis and asthma, showed converging evidence from both rare and common variants. 91 genes exerted significant effects on longitudinal outcomes (interquartile range of Hazard Ratio: 1.12-5.89). Mendelian randomization identified five causal genes, of which four were approved drug targets (CDSN, DDR1, LTA, and IL18BP). Proteomic analysis indicated that mutations associated with specific IMDs might also affect protein expression in other IMDs. For example, DXO (celiac disease-related gene) and PSMB9 (alopecia areata-related gene) could modulate CDSN (autoimmune hypothyroidism-, psoriasis-, asthma-, and Graves' disease-related gene) expression. Identified genes predominantly impact immune and biochemical processes, and can be clustered into pathways of immune-related, urate metabolism, and antigen processing. Our findings identified protein-coding variants which are the key to IMDs pathogenesis and provided new insights into tailored innovative therapies.
Collapse
Affiliation(s)
- Liu Yang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200040, China
| | - Ya-Nan Ou
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, 266071, China
| | - Bang-Sheng Wu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200040, China
| | - Wei-Shi Liu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200040, China
| | - Yue-Ting Deng
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200040, China
| | - Xiao-Yu He
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200040, China
| | - Yi-Lin Chen
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200040, China
| | - Jujiao Kang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200443, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Chen-Jie Fei
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200040, China
| | - Ying Zhu
- State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudan University, Shanghai, 200032, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, 266071, China
| | - Qiang Dong
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200040, China
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200443, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Wei Cheng
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200040, China
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200443, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China
| | - Jin-Tai Yu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200040, China.
| |
Collapse
|
111
|
Tsetsos F, Topaloudi A, Jain P, Yang Z, Yu D, Kolovos P, Tumer Z, Rizzo R, Hartmann A, Depienne C, Worbe Y, Müller-Vahl KR, Cath DC, Boomsma DI, Wolanczyk T, Zekanowski C, Barta C, Nemoda Z, Tarnok Z, Padmanabhuni SS, Buxbaum JD, Grice D, Glennon J, Stefansson H, Hengerer B, Yannaki E, Stamatoyannopoulos JA, Benaroya-Milshtein N, Cardona F, Hedderly T, Heyman I, Huyser C, Mir P, Morer A, Mueller N, Munchau A, Plessen KJ, Porcelli C, Roessner V, Walitza S, Schrag A, Martino D, Tischfield JA, Heiman GA, Willsey AJ, Dietrich A, Davis LK, Crowley JJ, Mathews CA, Scharf JM, Georgitsi M, Hoekstra PJ, Paschou P. Genome-Wide Association Study Points to Novel Locus for Gilles de la Tourette Syndrome. Biol Psychiatry 2024; 96:114-124. [PMID: 36738982 PMCID: PMC10783199 DOI: 10.1016/j.biopsych.2023.01.023] [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: 05/11/2022] [Revised: 11/23/2022] [Accepted: 01/24/2023] [Indexed: 02/05/2023]
Abstract
BACKGROUND Tourette syndrome (TS) is a childhood-onset neurodevelopmental disorder of complex genetic architecture and is characterized by multiple motor tics and at least one vocal tic persisting for more than 1 year. METHODS We performed a genome-wide meta-analysis integrating a novel TS cohort with previously published data, resulting in a sample size of 6133 individuals with TS and 13,565 ancestry-matched control participants. RESULTS We identified a genome-wide significant locus on chromosome 5q15. Integration of expression quantitative trait locus, Hi-C (high-throughput chromosome conformation capture), and genome-wide association study data implicated the NR2F1 gene and associated long noncoding RNAs within the 5q15 locus. Heritability partitioning identified statistically significant enrichment in brain tissue histone marks, while polygenic risk scoring of brain volume data identified statistically significant associations with right and left thalamus volumes and right putamen volume. CONCLUSIONS Our work presents novel insights into the neurobiology of TS, thereby opening up new directions for future studies.
Collapse
Affiliation(s)
- Fotis Tsetsos
- Department of Molecular Biology and Genetics, Democritus University of Thrace, Alexandroupolis, Greece
| | - Apostolia Topaloudi
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA
| | - Pritesh Jain
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA
| | - Zhiyu Yang
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA
| | - Dongmei Yu
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Petros Kolovos
- Department of Molecular Biology and Genetics, Democritus University of Thrace, Alexandroupolis, Greece
| | - Zeynep Tumer
- Department of Clinical Genetics, Kennedy Center, Copenhagen University Hospital, Rigshospitalet, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen
| | - Renata Rizzo
- Child and Adolescent Neurology and Psychiatry, Department of Clinical and Experimental Medicine, University of Catania, Catania, Italy
| | - Andreas Hartmann
- Department of Neurology, Hôpital de la Pitié-Salpêtrière, Paris, France
| | - Christel Depienne
- Institute for Human Genetics, University Hospital Essen, Essen, Germany
| | - Yulia Worbe
- Assistance Publique Hôpitaux de Paris, Hopital Saint Antoine, Paris France
- French Reference Centre for Gilles de la Tourette Syndrome, Groupe Hospitalier Pitié-Salpêtrière, Paris, France
| | - Kirsten R. Müller-Vahl
- Department of Psychiatry, Social psychiatry and Psychotherapy, Hannover Medical School, Hannover, Germany
| | - Danielle C. Cath
- Department of Clinical and health Psychology, Utrecht University, Utrecht, Netherlands
| | - Dorret I. Boomsma
- Institute for Anatomy and Cell Biology, Ulm University, Ulm, Germany
- EMGO+ Institute for Health and Care Research, VU University Medical Centre, Amsterdam, Netherlands
| | - Tomasz Wolanczyk
- Department of Child Psychiatry, Medical University of Warsaw, Warsaw, Poland
| | - Cezary Zekanowski
- Laboratory of Neurogenetics, Department of Neurodegenerative Disorders, Mossakowski Medical Research Institute, Polish Academy of Sciences, Warsaw, Poland
| | - Csaba Barta
- Department of Molecular Biology, Institute of Biochemistry and Molecular Biology, Semmelweis University, Budapest, Hungary
| | - Zsofia Nemoda
- Department of Molecular Biology, Institute of Biochemistry and Molecular Biology, Semmelweis University, Budapest, Hungary
| | - Zsanett Tarnok
- Vadaskert Clinic for Child and Adolescent Psychiatry, Hungary
| | | | - Joseph D. Buxbaum
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, USA
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, USA
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, USA
| | - Dorothy Grice
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, USA
- The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, USA
- Division of Tics, OCD, and Related Disorders, Icahn School of Medicine at Mount Sinai, USA
| | - Jeffrey Glennon
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Netherlands
| | | | - Bastian Hengerer
- Boehringer Ingelheim Pharma GmbH & Co. KG, CNS Research, Germany
| | - Evangelia Yannaki
- Hematology Department- Hematopoietic Cell Transplantation Unit, Gene and Cell Therapy Center, George Papanikolaou Hospital, Greece
- Department of Medicine, University of Washington, WA, USA
| | - John A. Stamatoyannopoulos
- Altius Institute for Biomedical Sciences, WA, USA
- Department of Genome Sciences, University of Washington, WA, USA
- Department of Medicine, Division of Oncology, University of Washington, WA, USA
| | - Noa Benaroya-Milshtein
- Child and Adolescent Psychiatry Department, Schneider Children’s Medical Centre of Israel, Petah-Tikva. Affiliated to Sackler Faculty of Medicine, Tel Aviv University, Israel
| | - Francesco Cardona
- Department of Human Neurosciences, University La Sapienza of Rome, Rome, Italy
| | - Tammy Hedderly
- Evelina London Children’s Hospital GSTT, Kings Health Partners AHSC, London, UK
| | - Isobel Heyman
- Psychological Medicine, Great Ormond Street Hospital NHS Foundation Trust, Great Ormond Street, London, UK
| | - Chaim Huyser
- Levvel, Academic Center for Child and Adolescent Psychiatry, Amsterdam, The Netherlands
- Amsterdam UMC, Department of Child and Adolescent Psychiatry, Amsterdam, The Netherlands
| | - Pablo Mir
- Unidad de Trastornos del Movimiento. Instituto de Biomedicina de Sevilla (IBiS). Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla. Seville, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Astrid Morer
- Department of Child and Adolescent Psychiatry and Psychology, Institute of Neurosciences, Hospital Clinic Universitari, Barcelona, Spain
- Institut d’Investigacions Biomediques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Centro de Investigacion en Red de Salud Mental (CIBERSAM), Instituto Carlos III, Spain
| | - Norbert Mueller
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Alexander Munchau
- Institute of Systems Motor Science, University of Lübeck, Lübeck, Germany
| | - Kerstin J Plessen
- Child and Adolescent Mental Health Centre, Mental Health Services, Capital Region of Denmark and University of Copenhagen, Copenhagen, Denmark
- Division of Child and Adolescent Psychiatry, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland
| | - Cesare Porcelli
- ASL BA, Maternal and Childood Department; Adolescence and Childhood Neuropsychiatry Unit; Bari, Italy
| | - Veit Roessner
- Department of Child and Adolescent Psychiatry, Medical Faculty Carl Gustav Carus, TU Dresden, Dresden, Germany
| | - Susanne Walitza
- Department of Child and Adolescent Psychiatry and Psychotherapy, University of Zurich, Zurich, Switzerland
| | - Anette Schrag
- Department of Clinical Neuroscience, UCL Institute of Neurology, University College London, London, UK
| | - Davide Martino
- Department of Clinical Neurosciences, Cumming School of Medicine & Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | | | | | | | | | | | | | - Jay A. Tischfield
- Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers, the State University of New Jersey, Piscataway, NJ, USA
| | - Gary A. Heiman
- Department of Genetics and the Human Genetics Institute of New Jersey, Rutgers, the State University of New Jersey, Piscataway, NJ, USA
| | - A. Jeremy Willsey
- Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
- Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Andrea Dietrich
- University of Groningen, University Medical Centre Groningen, Department of Child and Adolescent Psychiatry, Groningen, the Netherlands
| | - Lea K. Davis
- Division of Genetic Medicine, Department of Medicine Vanderbilt University Medical Center Nashville, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - James J. Crowley
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Carol A. Mathews
- Department of Psychiatry and Genetics Institute, University of Florida College of Medicine, USA
| | - Jeremiah M. Scharf
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Neurology, Brigham and Women’s Hospital, and the Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Marianthi Georgitsi
- Department of Molecular Biology and Genetics, Democritus University of Thrace, Alexandroupolis, Greece
- 1st Laboratory of Medical Biology-Genetics, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Pieter J. Hoekstra
- University of Groningen, University Medical Centre Groningen, Department of Child and Adolescent Psychiatry, Groningen, the Netherlands
| | - Peristera Paschou
- Department of Biological Sciences, Purdue University, West Lafayette, IN, USA
| |
Collapse
|
112
|
Giordano A, Clarelli F, Pignolet B, Mascia E, Sorosina M, Misra K, Ferrè L, Bucciarelli F, Manouchehrinia A, Moiola L, Martinelli V, Rocca MA, Liblau R, Filippi M, Esposito F. Vitamin D affects the risk of disease activity in multiple sclerosis. J Neurol Neurosurg Psychiatry 2024:jnnp-2024-334062. [PMID: 39004505 DOI: 10.1136/jnnp-2024-334062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/16/2024] [Accepted: 06/19/2024] [Indexed: 07/16/2024]
Abstract
BACKGROUND Vitamin D (VitD) affects the risk of multiple sclerosis (MS), but the impact on disease activity is controversial. We assessed whether VitD is associated with the No-Evidence of Disease Activity-3 (NEDA-3) status at 2 years from disease-modifying treatment (DMT) start, and whether this association is causal or the result of confounding factors. Furthermore, we explored if a genetic predisposition to higher VitD levels affects the risk of disease activity. METHODS 230 untreated relapsing-remitting MS patients underwent serum 25-OH-vitamin-D measurement, and the association between seasonally adjusted VitD and disease activity was tested. Modelling a Polygenic Risk Score from a Genome-Wide Association Study on ~400 000 individuals, we studied the impact of genetic predisposition to higher VitD on the NEDA-3 status in 1408 independent MS patients. Two-sample Mendelian randomisation (MR) was used to assess causality. RESULTS Lower baseline VitD was associated with decreased probability of NEDA-3 at 2 years (p=0.019). Particularly, VitD levels <20 ng/mL conferred an over twofold risk of disease activity (OR 2.36, 95% CI 1.30 to 3.88, p=0.0037). Genetic predisposition to higher VitD levels was associated with delayed age at MS onset (p=0.018) and with a higher probability of NEDA-3 status (p=0.034). MR confirmed causality between VitD and the risk of disease activity (p=0.041). CONCLUSIONS VitD levels before DMT start affect the risk of disease activity in MS. Genetic predisposition to higher VitD levels confers a lower risk of disease activity and is associated with delayed MS onset. Our work prompts future prospective studies regarding VitD supplementation and lifestyle interventions to hamper disease activity in MS.
Collapse
Affiliation(s)
- Antonino Giordano
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Università Vita Salute San Raffaele, Milano, Italy
- Department of Neurology and MS Center, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Ferdinando Clarelli
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Béatrice Pignolet
- Toulouse Institute for Infectious and Inflammatory Diseases (Infinity), University of Toulouse, CNRS, INSERM, Toulouse, France
- Neurosciences Department, Toulouse University Hospital, Toulouse, France
| | - Elisabetta Mascia
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Melissa Sorosina
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Kaalindi Misra
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Laura Ferrè
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Department of Neurology and MS Center, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Florence Bucciarelli
- Toulouse Institute for Infectious and Inflammatory Diseases (Infinity), University of Toulouse, CNRS, INSERM, Toulouse, France
| | | | - Lucia Moiola
- Department of Neurology and MS Center, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Vittorio Martinelli
- Department of Neurology and MS Center, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Maria A Rocca
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Università Vita Salute San Raffaele, Milano, Italy
- Department of Neurology and MS Center, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Roland Liblau
- Toulouse Institute for Infectious and Inflammatory Diseases (Infinity), University of Toulouse, CNRS, INSERM, Toulouse, France
- Department of Immunology, Toulouse University Hospitals, Toulouse, France
| | - Massimo Filippi
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Università Vita Salute San Raffaele, Milano, Italy
- Department of Neurology and MS Center, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Federica Esposito
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- Department of Neurology and MS Center, IRCCS Ospedale San Raffaele, Milan, Italy
| |
Collapse
|
113
|
Hong H, Mocci E, Kamp K, Zhu S, Cain KC, Burr RL, Perry JA, Heitkemper MM, Weaver-Toedtman KR, Dorsey SG. Genetic Variations in TrkB.T1 Isoform and Their Association With Somatic and Psychological Symptoms in Individuals With IBS. THE JOURNAL OF PAIN 2024:104634. [PMID: 39004388 DOI: 10.1016/j.jpain.2024.104634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Revised: 06/13/2024] [Accepted: 06/19/2024] [Indexed: 07/16/2024]
Abstract
Irritable bowel syndrome (IBS), a disorder of gut-brain interaction, is often comorbid with somatic pain and psychological disorders. Dysregulated signaling of brain-derived neurotrophic factor (BDNF) and its receptor, tropomyosin-related kinase B (TrkB), has been implicated in somatic-psychological symptoms in individuals with IBS. We investigated the association of 10 single-nucleotide polymorphisms (SNPs) in the regulatory 3' untranslated region of neurotrophic receptor tyrosine kinase-2 (NTRK2) kinase domain-deficient truncated isoform (TrkB.T1) and BDNF Val66Met SNP with somatic and psychological symptoms and quality-of-life (QoL) in a cohort from the United States (IBS, n = 464; healthy controls, n = 156). We found that the homozygous recessive genotype (G/G) of rs2013566 in individuals with IBS is associated with worsened somatic symptoms, including headache, back pain, joint pain, muscle pain, and somatization as well as diminished sleep quality, energy level, and overall QoL. Validation using United Kingdom BioBank data confirmed the association of rs2013566 with an increased likelihood of headache. Several SNPs (rs1627784, rs1624327, and rs1147198) showed significant associations with muscle pain in our U.S. cohort. These 4 SNPs are predominantly located in H3K4Me1-enriched regions, suggesting their enhancer and/or transcription regulation potential. Our findings suggest that genetic variation within the 3' untranslated region region of the TrkB.T1 isoform may contribute to comorbid conditions in individuals with IBS, resulting in a spectrum of somatic and psychological symptoms impacting their QoL. These findings advance our understanding of the genetic interaction between BDNF/TrkB pathways and somatic-psychological symptoms in IBS, highlighting the importance of further exploring this interaction for potential clinical applications. PERSPECTIVE: This study aims to understand the genetic effects on IBS-related symptoms across somatic, psychological, and quality-of-life (QoL) domains, validated by United Kingdom BioBank data. The rs2013566 homozygous recessive genotype correlates with worsened somatic symptoms and reduced QoL, emphasizing its clinical significance.
Collapse
Affiliation(s)
- Hyejeong Hong
- Department of Biobehavioral Health Sciences, University of Pennsylvania School of Nursing, Philadelphia, PA
| | - Evelina Mocci
- Department of Pain and Translational Symptom Science, University of Maryland School of Nursing, Baltimore, MD
| | - Kendra Kamp
- Department of Biobehavioral Nursing and Health Informatics, University of Washington School of Nursing, Seattle, WA
| | - Shijun Zhu
- Department of Organizational Systems and Adult Health, University of Maryland School of Nursing, Baltimore, MD
| | - Kevin C Cain
- Department of Biostatistics, University of Washington School of Nursing, Seattle, WA
| | - Robert L Burr
- Department of Biobehavioral Nursing and Health Informatics, University of Washington School of Nursing, Seattle, WA
| | - James A Perry
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD
| | - Margaret M Heitkemper
- Department of Biobehavioral Nursing and Health Informatics, University of Washington School of Nursing, Seattle, WA
| | - Kristen R Weaver-Toedtman
- Department of Biobehavioral Health and Nursing Science, University of South Carolina College of Nursing, Columbia, SC
| | - Susan G Dorsey
- Department of Pain and Translational Symptom Science, University of Maryland School of Nursing, Baltimore, MD.
| |
Collapse
|
114
|
Yu Y, Yang X, Liu D, Du P, Meng H, Huang Z, Xiong J, Ding Y, Ren X, Allen E, Wang H, Han S, Jin L, Wang CC, Wen S. Ancient genomic analysis of a Chinese hereditary elite from the Northern and Southern Dynasties. J Genet Genomics 2024:S1673-8527(24)00184-X. [PMID: 39009302 DOI: 10.1016/j.jgg.2024.07.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 07/01/2024] [Accepted: 07/04/2024] [Indexed: 07/17/2024]
Abstract
China's Northern and Southern Dynasties period (3rd-6th centuries AD) marked a significant era of ethnic integration in northern China. However, previous ancient DNA studies have primarily focused on northern ethnic groups, with limited research on the genetic formation of the hereditary elite family, especially considering their abundant archaeological record and clear material identity. In this study, we obtained the ancient genome of a hereditary elite family, Gao Bin (, 503-572 AD), at 0.6473-fold coverage with 475132 single-nucleotide polymorphisms (SNPs) on the 1240k panel. His mitochondrial haplogroup belonged to Z4 and Y-haplogroup to O1a1a2b-F2444*. The genetic profile of Gao Bin was most similar to that of the northern Han Chinese. He could be modelled as deriving all his ancestry from Late Neolithic to Iron Age Yellow River farmers without influence from Northeast Asia, Korea, or the Mongolian Plateau. Our study sheds light on the genetic formation of hereditary elite families in the context of the Southern and Northern Dynasties ethnic integration.
Collapse
Affiliation(s)
- Yao Yu
- Institute of Archaeological Science, Fudan University, Shanghai 200433, China; Department of History, Fudan University, Shanghai 200433, China
| | - Xiaomin Yang
- Department of Anthropology and Ethnology, Institute of Anthropology, Fujian Provincial Key Laboratory of Philosophy and Social Sciences in Bioanthropology, School of Sociology and Anthropology, Xiamen University, Xiamen, Fujian 361005, China
| | - Daiyun Liu
- Shaanxi Academy of Archaeology, Xi'an, Shaanxi 710054, China
| | - Panxin Du
- Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai 200433, China; State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, and Human Phenome Institute, Fudan University, Shanghai 200433, China
| | - Hailiang Meng
- Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Zixiao Huang
- Department of History, Fudan University, Shanghai 200433, China
| | - Jianxue Xiong
- Institute of Archaeological Science, Fudan University, Shanghai 200433, China
| | - Yi Ding
- Institute of Archaeological Science, Fudan University, Shanghai 200433, China
| | - Xiaoying Ren
- Institute of Archaeological Science, Fudan University, Shanghai 200433, China
| | - Edward Allen
- Institute of Archaeological Science, Fudan University, Shanghai 200433, China
| | - Hui Wang
- Center for the Belt and Road Archaeology and Ancient Civilizations, Shanghai 200433, China
| | - Sheng Han
- Department of History, Fudan University, Shanghai 200433, China
| | - Li Jin
- Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai 200433, China.
| | - Chuan-Chao Wang
- Department of Anthropology and Ethnology, Institute of Anthropology, Fujian Provincial Key Laboratory of Philosophy and Social Sciences in Bioanthropology, School of Sociology and Anthropology, Xiamen University, Xiamen, Fujian 361005, China; State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, Fujian 361102, China; State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen, Fujian 361102, China; Institute of Artificial Intelligence, Xiamen University, Xiamen, Fujian 361005, China.
| | - Shaoqing Wen
- Institute of Archaeological Science, Fudan University, Shanghai 200433, China; Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai 200433, China; Center for the Belt and Road Archaeology and Ancient Civilizations, Shanghai 200433, China; MOE Laboratory for National Development and Intelligent Governance, Fudan University, Shanghai 200433, China.
| |
Collapse
|
115
|
Shen Q, Wu Z, Zan J, Yang X, Guo J, Ji Z, Wang B, Liu Y, Mao X, Wang X, Zou X, Zhou H, Peng Y, Ma H, He H, Bai T, Xu M, Wen S, Jin L, Zhang Q, Wang CC. Ancient genomes illuminate the demographic history of Shandong over the past two millennia. J Genet Genomics 2024:S1673-8527(24)00185-1. [PMID: 39009303 DOI: 10.1016/j.jgg.2024.07.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Revised: 07/01/2024] [Accepted: 07/07/2024] [Indexed: 07/17/2024]
Abstract
Shandong province, located in the Lower Yellow River, is one of the birthplaces of ancient Chinese civilization. However, the comprehensive genetic histories of this region have remained largely unknown until now due to a lack of ancient human genomes. Here, we present 21 ancient genomes from Shandong dating from the Warring States period to the Jin-Yuan Dynasties. Unlike the early Neolithic samples from Shandong, the historical samples are most closely related to post-Late Neolithic populations of the Middle Yellow River Basin, suggesting a population turnover in Shandong from the Neolithic Age to the Historical era. In addition, we detect a close genetic affinity between the historical samples in Shandong and present-day Han Chinese, showing long-term genetic stability in Han Chinese at least since the Warring States period.
Collapse
Affiliation(s)
- Qu Shen
- Department of Anthropology and Ethnology, Institute of Anthropology, Fujian Provincial Key Laboratory of Philosophy and Social Sciences in Bioanthropology, School of Sociology and Anthropology, Xiamen University, Xiamen, Fujian 361005, China
| | - Zhigang Wu
- Shandong Provincial Institute of Cultural Relics and Archaeology, Jinan, Shandong 250012, China.
| | - Jinguo Zan
- Shandong Provincial Institute of Cultural Relics and Archaeology, Jinan, Shandong 250012, China
| | - Xiaomin Yang
- Department of Anthropology and Ethnology, Institute of Anthropology, Fujian Provincial Key Laboratory of Philosophy and Social Sciences in Bioanthropology, School of Sociology and Anthropology, Xiamen University, Xiamen, Fujian 361005, China.
| | - Jianxin Guo
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650201, China
| | - Zhi Ji
- Department of Anthropology and Ethnology, Institute of Anthropology, Fujian Provincial Key Laboratory of Philosophy and Social Sciences in Bioanthropology, School of Sociology and Anthropology, Xiamen University, Xiamen, Fujian 361005, China
| | - Baitong Wang
- Department of Anthropology and Ethnology, Institute of Anthropology, Fujian Provincial Key Laboratory of Philosophy and Social Sciences in Bioanthropology, School of Sociology and Anthropology, Xiamen University, Xiamen, Fujian 361005, China
| | - Yilan Liu
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, Fujian 361002, China
| | - Xiaolu Mao
- Department of Anthropology and Ethnology, Institute of Anthropology, Fujian Provincial Key Laboratory of Philosophy and Social Sciences in Bioanthropology, School of Sociology and Anthropology, Xiamen University, Xiamen, Fujian 361005, China
| | - Xinyi Wang
- Department of Anthropology and Ethnology, Institute of Anthropology, Fujian Provincial Key Laboratory of Philosophy and Social Sciences in Bioanthropology, School of Sociology and Anthropology, Xiamen University, Xiamen, Fujian 361005, China
| | - Xinyue Zou
- Department of Anthropology and Ethnology, Institute of Anthropology, Fujian Provincial Key Laboratory of Philosophy and Social Sciences in Bioanthropology, School of Sociology and Anthropology, Xiamen University, Xiamen, Fujian 361005, China
| | - Hongming Zhou
- Department of Anthropology and Ethnology, Institute of Anthropology, Fujian Provincial Key Laboratory of Philosophy and Social Sciences in Bioanthropology, School of Sociology and Anthropology, Xiamen University, Xiamen, Fujian 361005, China
| | - Yanying Peng
- Department of Anthropology and Ethnology, Institute of Anthropology, Fujian Provincial Key Laboratory of Philosophy and Social Sciences in Bioanthropology, School of Sociology and Anthropology, Xiamen University, Xiamen, Fujian 361005, China
| | - Hao Ma
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, Fujian 361002, China
| | - Haifeng He
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, Fujian 361002, China
| | - Tianyou Bai
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, Fujian 361002, China
| | - Mengting Xu
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, Fujian 361002, China
| | - Shaoqing Wen
- Institute of Archaeological Science, Fudan University, Shanghai 200438, China
| | - Li Jin
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Shanghai 200433, China; Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Qun Zhang
- Department of Archaeology, School of History, Wuhan University, Wuhan, Hubei 430072, China.
| | - Chuan-Chao Wang
- Department of Anthropology and Ethnology, Institute of Anthropology, Fujian Provincial Key Laboratory of Philosophy and Social Sciences in Bioanthropology, School of Sociology and Anthropology, Xiamen University, Xiamen, Fujian 361005, China; State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Xiamen University, Xiamen, Fujian 361002, China; Ministry of Education Key Laboratory of Contemporary Anthropology, Department of Anthropology and Human Genetics, School of Life Sciences, Fudan University, Shanghai 200433, China.
| |
Collapse
|
116
|
Landis JB, Guercio AM, Brown KE, Fiscus CJ, Morrell PL, Koenig D. Natural selection drives emergent genetic homogeneity in a century-scale experiment with barley. Science 2024; 385:eadl0038. [PMID: 38991084 DOI: 10.1126/science.adl0038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 05/21/2024] [Indexed: 07/13/2024]
Abstract
Direct observation is central to our understanding of adaptation, but evolution is rarely documented in a large, multicellular organism for more than a few generations. In this study, we observed evolution across a century-scale competition experiment, barley composite cross II (CCII). CCII was founded in 1929 in Davis, California, with thousands of genotypes, but we found that natural selection has massively reduced genetic diversity, leading to a single lineage constituting most of the population by generation 50. Selection favored alleles originating from climates similar to that of Davis and targeted loci contributing to reproductive development, including the barley diversification loci Vrs1, HvCEN, Ppd-H1, and Vrn-H2. Our findings point to selection as the predominant force shaping genomic variation in one of the world's oldest biological experiments.
Collapse
Affiliation(s)
- Jacob B Landis
- Department of Botany and Plant Sciences, University of California, Riverside, CA 92521, USA
| | - Angelica M Guercio
- Department of Botany and Plant Sciences, University of California, Riverside, CA 92521, USA
| | - Keely E Brown
- Department of Botany and Plant Sciences, University of California, Riverside, CA 92521, USA
| | - Christopher J Fiscus
- Department of Botany and Plant Sciences, University of California, Riverside, CA 92521, USA
| | - Peter L Morrell
- Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN 55108, USA
| | - Daniel Koenig
- Department of Botany and Plant Sciences, University of California, Riverside, CA 92521, USA
- Institute for Integrative Genome Biology, University of California, Riverside, CA 92521, USA
| |
Collapse
|
117
|
Fernandez MV, Liu M, Beric A, Johnson M, Cetin A, Patel M, Budde J, Kohlfeld P, Bergmann K, Lowery J, Flynn A, Brock W, Sanchez Montejo B, Gentsch J, Sykora N, Norton J, Gentsch J, Valdez O, Gorijala P, Sanford J, Sun Y, Wang C, Western D, Timsina J, Mangetti Goncalves T, Do AN, Sung YJ, Zhao G, Morris JC, Moulder K, Holtzman DM, Bateman RJ, Karch C, Hassenstab J, Xiong C, Schindler SE, Balls-Berry JJ, Benzinger TLS, Perrin RJ, Denny A, Snider BJ, Stark SL, Ibanez L, Cruchaga C. Genetic and multi-omic resources for Alzheimer disease and related dementia from the Knight Alzheimer Disease Research Center. Sci Data 2024; 11:768. [PMID: 38997326 PMCID: PMC11245521 DOI: 10.1038/s41597-024-03485-9] [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: 01/24/2024] [Accepted: 06/06/2024] [Indexed: 07/14/2024] Open
Abstract
The Knight-Alzheimer Disease Research Center (Knight-ADRC) at Washington University in St. Louis has pioneered and led worldwide seminal studies that have expanded our clinical, social, pathological, and molecular understanding of Alzheimer Disease. Over more than 40 years, research volunteers have been recruited to participate in cognitive, neuropsychologic, imaging, fluid biomarkers, genomic and multi-omic studies. Tissue and longitudinal data collected to foster, facilitate, and support research on dementia and aging. The Genetics and high throughput -omics core (GHTO) have collected of more than 26,000 biological samples from 6,625 Knight-ADRC participants. Samples available include longitudinal DNA, RNA, non-fasted plasma, cerebrospinal fluid pellets, and peripheral blood mononuclear cells. The GHTO has performed deep molecular profiling (genomic, transcriptomic, epigenomic, proteomic, and metabolomic) from large number of brain (n = 2,117), CSF (n = 2,012) and blood/plasma (n = 8,265) samples with the goal of identifying novel risk and protective variants, identify novel molecular biomarkers and causal and druggable targets. Overall, the resources available at GHTO support the increase of our understanding of Alzheimer Disease.
Collapse
Affiliation(s)
- Maria Victoria Fernandez
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Research Center and Memory Clinic, ACE Alzheimer Center, Barcelona, Spain
| | - Menghan Liu
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Aleksandra Beric
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Matt Johnson
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Arda Cetin
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Maulik Patel
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - John Budde
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Pat Kohlfeld
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Kristy Bergmann
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Joseph Lowery
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Allison Flynn
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - William Brock
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Brenda Sanchez Montejo
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Jen Gentsch
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Nicholas Sykora
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Joanne Norton
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Jen Gentsch
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Olga Valdez
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Priyanka Gorijala
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Jessie Sanford
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Yichen Sun
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Ciyang Wang
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Dan Western
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Jigyasha Timsina
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | | | - Anh N Do
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Yun Ju Sung
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Guoyan Zhao
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Pathology and Immunology Department, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - John C Morris
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Krista Moulder
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - David M Holtzman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Randall J Bateman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
- Dominantly Inherited Alzheimer Disease Network (DIAN), St. Louis, USA
| | - Celeste Karch
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
- Dominantly Inherited Alzheimer Disease Network (DIAN), St. Louis, USA
| | - Jason Hassenstab
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Chengjie Xiong
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Dominantly Inherited Alzheimer Disease Network (DIAN), St. Louis, USA
| | - Suzanne E Schindler
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Joyce Joy Balls-Berry
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Tammie L S Benzinger
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Dominantly Inherited Alzheimer Disease Network (DIAN), St. Louis, USA
- Radiology Department, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Richard J Perrin
- Pathology and Immunology Department, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Dominantly Inherited Alzheimer Disease Network (DIAN), St. Louis, USA
| | - Andrea Denny
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - B Joy Snider
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Susan L Stark
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Occupational Therapy, Neurology and Social Work, St. Louis, USA
| | - Laura Ibanez
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA.
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA.
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA.
- Dominantly Inherited Alzheimer Disease Network (DIAN), St. Louis, USA.
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA.
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA.
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA.
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA.
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA.
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA.
- Dominantly Inherited Alzheimer Disease Network (DIAN), St. Louis, USA.
| |
Collapse
|
118
|
Tong W, Wang Y, Li F, Zhai F, Su J, Wu D, Yi L, Gao Q, Wu Q, Xia E. Genomic variation of 363 diverse tea accessions unveils the genetic diversity, domestication, and structural variations associated with tea adaptation. JOURNAL OF INTEGRATIVE PLANT BIOLOGY 2024. [PMID: 38990113 DOI: 10.1111/jipb.13737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Accepted: 06/14/2024] [Indexed: 07/12/2024]
Abstract
Domestication has shaped the population structure and agronomic traits of tea plants, yet the complexity of tea population structure and genetic variation that determines these traits remains unclear. We here investigated the resequencing data of 363 diverse tea accessions collected extensively from almost all tea distributions and found that the population structure of tea plants was divided into eight subgroups, which were basically consistent with their geographical distributions. The genetic diversity of tea plants in China decreased from southwest to east as latitude increased. Results also indicated that Camellia sinensis var. assamica (CSA) illustrated divergent selection signatures with Camellia sinensis var. sinensis (CSS). The domesticated genes of CSA were mainly involved in leaf development, flavonoid and alkaloid biosynthesis, while the domesticated genes in CSS mainly participated in amino acid metabolism, aroma compounds biosynthesis, and cold stress. Comparative population genomics further identified ~730 Mb novel sequences, generating 6,058 full-length protein-encoding genes, significantly expanding the gene pool of tea plants. We also discovered 217,376 large-scale structural variations and 56,583 presence and absence variations (PAVs) across diverse tea accessions, some of which were associated with tea quality and stress resistance. Functional experiments demonstrated that two PAV genes (CSS0049975 and CSS0006599) were likely to drive trait diversification in cold tolerance between CSA and CSS tea plants. The overall findings not only revealed the genetic diversity and domestication of tea plants, but also underscored the vital role of structural variations in the diversification of tea plant traits.
Collapse
Affiliation(s)
- Wei Tong
- State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, 230036, China
| | - Yanli Wang
- State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, 230036, China
| | - Fangdong Li
- State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, 230036, China
- School of Information and Artificial Intelligence, Anhui Agricultural University, Hefei, 230036, China
| | - Fei Zhai
- State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, 230036, China
| | - Jingjing Su
- State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, 230036, China
| | - Didi Wu
- State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, 230036, China
| | - Lianghui Yi
- State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, 230036, China
| | - Qijuan Gao
- State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, 230036, China
- School of Computer and Artificial Intelligence, Hefei Normal University, Hefei, 230061, China
| | - Qiong Wu
- Tea Research Institute, Anhui Academy of Agricultural Sciences, Hefei, 230031, China
| | - Enhua Xia
- State Key Laboratory of Tea Plant Biology and Utilization, Anhui Agricultural University, Hefei, 230036, China
| |
Collapse
|
119
|
Monti R, Eick L, Hudjashov G, Läll K, Kanoni S, Wolford BN, Wingfield B, Pain O, Wharrie S, Jermy B, McMahon A, Hartonen T, Heyne H, Mars N, Lambert S, Hveem K, Inouye M, van Heel DA, Mägi R, Marttinen P, Ripatti S, Ganna A, Lippert C. Evaluation of polygenic scoring methods in five biobanks shows larger variation between biobanks than methods and finds benefits of ensemble learning. Am J Hum Genet 2024; 111:1431-1447. [PMID: 38908374 PMCID: PMC11267524 DOI: 10.1016/j.ajhg.2024.06.003] [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: 11/20/2023] [Revised: 05/31/2024] [Accepted: 06/05/2024] [Indexed: 06/24/2024] Open
Abstract
Methods of estimating polygenic scores (PGSs) from genome-wide association studies are increasingly utilized. However, independent method evaluation is lacking, and method comparisons are often limited. Here, we evaluate polygenic scores derived via seven methods in five biobank studies (totaling about 1.2 million participants) across 16 diseases and quantitative traits, building on a reference-standardized framework. We conducted meta-analyses to quantify the effects of method choice, hyperparameter tuning, method ensembling, and the target biobank on PGS performance. We found that no single method consistently outperformed all others. PGS effect sizes were more variable between biobanks than between methods within biobanks when methods were well tuned. Differences between methods were largest for the two investigated autoimmune diseases, seropositive rheumatoid arthritis and type 1 diabetes. For most methods, cross-validation was more reliable for tuning hyperparameters than automatic tuning (without the use of target data). For a given target phenotype, elastic net models combining PGS across methods (ensemble PGS) tuned in the UK Biobank provided consistent, high, and cross-biobank transferable performance, increasing PGS effect sizes (β coefficients) by a median of 5.0% relative to LDpred2 and MegaPRS (the two best-performing single methods when tuned with cross-validation). Our interactively browsable online-results and open-source workflow prspipe provide a rich resource and reference for the analysis of polygenic scoring methods across biobanks.
Collapse
Affiliation(s)
- Remo Monti
- Hasso Plattner Institute, University of Potsdam, Digital Engineering Faculty, Potsdam, Germany; Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association, Berlin Institute for Medical Systems Biology, Berlin, Germany
| | - Lisa Eick
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Georgi Hudjashov
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Kristi Läll
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Stavroula Kanoni
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Brooke N Wolford
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway
| | - Benjamin Wingfield
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Oliver Pain
- Maurice Wohl Clinical Neuroscience Institute, Department of Basic and Clinical Neuroscience; Institute of Psychiatry, Psychology and Neuroscience; King's College London, London, UK
| | - Sophie Wharrie
- Aalto University, Department of Computer Science, Espoo, Finland
| | - Bradley Jermy
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Aoife McMahon
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Tuomo Hartonen
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Henrike Heyne
- Hasso Plattner Institute, University of Potsdam, Digital Engineering Faculty, Potsdam, Germany
| | - Nina Mars
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland; Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA; Stanley Center for Psychiatric Research and Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Samuel Lambert
- Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway; Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia; British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK; British Heart Foundation Cambridge Centre of Research Excellence, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway; Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway
| | - Michael Inouye
- Cambridge Baker Systems Genomics Initiative, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK; Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia; British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK; Victor Phillip Dahdaleh Heart and Lung Research Institute, University of Cambridge, Cambridge, UK; British Heart Foundation Cambridge Centre of Research Excellence, School of Clinical Medicine, University of Cambridge, Cambridge, UK; Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK
| | | | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Pekka Marttinen
- Aalto University, Department of Computer Science, Espoo, Finland
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland; Department of Public Health, University of Helsinki, Helsinki, Finland; Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Andrea Ganna
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland; Massachusetts General Hospital and Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Christoph Lippert
- Hasso Plattner Institute, University of Potsdam, Digital Engineering Faculty, Potsdam, Germany; Windreich Department of Artificial Intelligence and Human Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Diagnostic, Molecular, and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| |
Collapse
|
120
|
Du S, Chen J, Li J, Qian W, Wu S, Peng Q, Liu Y, Pan T, Li Y, Hadi SS, Tan J, Yuan Z, Wang J, Tang K, Wang Z, Wen Y, Dong X, Zhou W, Ruiz-Linares A, Shi Y, Jin L, Liu F, Zhang M, Wang S. A multi-ancestry GWAS meta-analysis of facial features and its application in predicting archaic human features. J Genet Genomics 2024:S1673-8527(24)00181-4. [PMID: 39002897 DOI: 10.1016/j.jgg.2024.07.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2024] [Revised: 07/06/2024] [Accepted: 07/06/2024] [Indexed: 07/15/2024]
Abstract
Facial morphology, a complex trait influenced by genetics, holds great significance in evolutionary research. However, due to limited fossil evidence, the facial characteristics of Neanderthals and Denisovans have remained largely unknown. In this study, we conducted a large-scale multi-ethnic meta-analysis of the genome-wide association study (GWAS), including 9674 East Asians and 10,115 Europeans, quantitatively assessing 78 facial traits using 3D facial images. We identified 71 genomic loci associated with facial features, including 21 novel loci. We developed a facial polygenic score (FPS) that enables the prediction of facial features based on genetic information. Interestingly, the distribution of FPSs among populations from diverse continental groups exhibited relevant correlations with observed facial features. Furthermore, we applied the FPS to predict the facial traits of seven Neanderthals and one Denisovan using ancient DNA and aligned predictions with the fossil records. Our results suggested that Neanderthals and Denisovans likely shared similar facial features, such as a wider but shorter nose and a wider endocanthion distance. The decreased mouth width was characterized specifically in Denisovans. The integration of genomic data and facial trait analysis provides valuable insights into the evolutionary history and adaptive changes in human facial morphology.
Collapse
Affiliation(s)
- Siyuan Du
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China; Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Jieyi Chen
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China; Center for Molecular Medicine, Pediatrics Research Institute, Children's Hospital of Fudan University, Shanghai 201102, China
| | - Jiarui Li
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China
| | - Wei Qian
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China
| | - Sijie Wu
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China
| | - Qianqian Peng
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China
| | - Yu Liu
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China
| | - Ting Pan
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Yi Li
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China
| | - Sibte Syed Hadi
- Department of Forensic Sciences, College of Criminal Justice, Naif Arab University for Security Sciences, Riyadh 11452, Kingdom of Saudi Arabia
| | - Jingze Tan
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200438, China
| | - Ziyu Yuan
- Fudan-Taizhou Institute of Health Sciences, Taizhou, Jiangsu 225326, China
| | - Jiucun Wang
- Fudan-Taizhou Institute of Health Sciences, Taizhou, Jiangsu 225326, China; Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200120, China; Research Unit of Dissecting the Population Genetics and Developing New Technologies for Treatment and Prevention of Skin Phenotypes and Dermatological Diseases (2019RU058), Chinese Academy of Medical Sciences, Shanghai 200438, China
| | - Kun Tang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China
| | - Zhuo Wang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Yanqin Wen
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Xinran Dong
- Center for Molecular Medicine, Pediatrics Research Institute, Children's Hospital of Fudan University, Shanghai 201102, China
| | - Wenhao Zhou
- Center for Molecular Medicine, Pediatrics Research Institute, Children's Hospital of Fudan University, Shanghai 201102, China; Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, Guangdong 510623, China
| | - Andrés Ruiz-Linares
- Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai 200438, China; Aix-Marseille Université, CNRS, EFS, ADES, Marseille 13005, France; Department of Genetics, Evolution and Environment, and UCL Genetics Institute, University College London, London WC1E 6BT, UK
| | - Yongyong Shi
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200030, China
| | - Li Jin
- Fudan-Taizhou Institute of Health Sciences, Taizhou, Jiangsu 225326, China; Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200120, China; Research Unit of Dissecting the Population Genetics and Developing New Technologies for Treatment and Prevention of Skin Phenotypes and Dermatological Diseases (2019RU058), Chinese Academy of Medical Sciences, Shanghai 200438, China
| | - Fan Liu
- Department of Forensic Sciences, College of Criminal Justice, Naif Arab University for Security Sciences, Riyadh 11452, Kingdom of Saudi Arabia; Department of Genetic Identification, Erasmus MC University Medical Center Rotterdam, 3015 CN Rotterdam, the Netherlands
| | - Manfei Zhang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China; Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai 200030, China; Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200120, China.
| | - Sijia Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai 200031, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, Yunnan 650223, China.
| |
Collapse
|
121
|
Gmel AI, Mikko S, Ricard A, Velie BD, Gerber V, Hamilton NA, Neuditschko M. Using high-density SNP data to unravel the origin of the Franches-Montagnes horse breed. Genet Sel Evol 2024; 56:53. [PMID: 38987703 PMCID: PMC11238448 DOI: 10.1186/s12711-024-00922-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Accepted: 07/03/2024] [Indexed: 07/12/2024] Open
Abstract
BACKGROUND The Franches-Montagnes (FM) is the last native horse breed of Switzerland, established at the end of the 19th century by cross-breeding local mares with Anglo-Norman stallions. We collected high-density SNP genotype data (Axiom™ 670 K Equine genotyping array) from 522 FM horses, including 44 old-type horses (OF), 514 European Warmblood horses (WB) from Sweden and Switzerland (including a stallion used for cross-breeding in 1990), 136 purebred Arabians (AR), 32 Shagya Arabians (SA), and 64 Thoroughbred (TB) horses, as introgressed WB stallions showed TB origin in their pedigrees. The aim of the study was to ascertain fine-scale population structures of the FM breed, including estimation of individual admixture levels and genomic inbreeding (FROH) by means of Runs of Homozygosity. RESULTS To assess fine-scale population structures within the FM breed, we applied a three-step approach, which combined admixture, genetic contribution, and FROH of individuals into a high-resolution network visualization. Based on this approach, we were able to demonstrate that population substructures, as detected by model-based clustering, can be either associated with a different genetic origin or with the progeny of most influential sires. Within the FM breed, admixed horses explained most of the genetic variance of the current breeding population, while OF horses only accounted for a small proportion of the variance. Furthermore, we illustrated that FM horses showed high TB admixture levels and we identified inconsistencies in the origin of FM horses descending from the Arabian stallion Doktryner. With the exception of WB, FM horses were less inbred compared to the other breeds. However, the relatively few but long ROH segments suggested diversity loss in both FM subpopulations. Genes located in FM- and OF-specific ROH islands had known functions involved in conformation and behaviour, two traits that are highly valued by breeders. CONCLUSIONS The FM remains the last native Swiss breed, clearly distinguishable from other historically introgressed breeds, but it suffered bottlenecks due to intensive selection of stallions, restrictive mating choices based on arbitrary definitions of pure breeding, and selection of rare coat colours. To preserve the genetic diversity of FM horses, future conservation managements strategies should involve a well-balanced selection of stallions (e.g., by integrating OF stallions in the FM breeding population) and avoid selection for rare coat colours.
Collapse
Affiliation(s)
- Annik Imogen Gmel
- Animal GenoPhenomics, Agroscope, Route de la Tioleyre 4, 1725, Posieux, Switzerland
- Equine Department, Vetsuisse Faculty, University of Zurich, Winterthurerstrasse 260, 8053, Zurich, Switzerland
| | - Sofia Mikko
- Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Box 7023, 750 07, Uppsala, Sweden
| | - Anne Ricard
- Institut National de la Recherche Agronomique, Domaine de Vilvert, 78350, Jouy-en-Josas, France
| | - Brandon D Velie
- Equine Genetics and Genomics Group, School of Life and Environmental Sciences, University of Sydney, RMC Gunn B19-603, Sydney, NSW, 2006, Australia
| | - Vinzenz Gerber
- Institut Suisse de Médecine Equine ISME, Vetsuisse Faculty, University of Bern, Länggassstrasse 124, 3012, Bern, Switzerland
| | - Natasha Anne Hamilton
- Sydney School of Veterinary Science, University of Sydney, Sydney, NSW, 2006, Australia
| | - Markus Neuditschko
- Animal GenoPhenomics, Agroscope, Route de la Tioleyre 4, 1725, Posieux, Switzerland.
| |
Collapse
|
122
|
vonHoldt BM, DeCandia AL, Cassidy KA, Stahler EE, Sinsheimer JS, Smith DW, Stahler DR. Patterns of reproduction and autozygosity distinguish the breeding from nonbreeding gray wolves of Yellowstone National Park. J Hered 2024; 115:327-338. [PMID: 37793153 PMCID: PMC11235126 DOI: 10.1093/jhered/esad062] [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: 03/25/2023] [Revised: 09/25/2023] [Accepted: 10/03/2023] [Indexed: 10/06/2023] Open
Abstract
For species of management concern, accurate estimates of inbreeding and associated consequences on reproduction are crucial for predicting their future viability. However, few studies have partitioned this aspect of genetic viability with respect to reproduction in a group-living social mammal. We investigated the contributions of foundation stock lineages, putative fitness consequences of inbreeding, and genetic diversity of the breeding versus nonreproductive segment of the Yellowstone National Park gray wolf population. Our dataset spans 25 years and seven generations since reintroduction, encompassing 152 nuclear families and 329 litters. We found more than 87% of the pedigree foundation genomes persisted and report influxes of allelic diversity from two translocated wolves from a divergent source in Montana. As expected for group-living species, mean kinship significantly increased over time but with minimal loss of observed heterozygosity. Strikingly, the reproductive portion of the population carried a significantly lower genome-wide inbreeding coefficients, autozygosity, and more rapid decay for linkage disequilibrium relative to the nonbreeding population. Breeding wolves had significantly longer lifespans and lower inbreeding coefficients than nonbreeding wolves. Our model revealed that the number of litters was negatively significantly associated with heterozygosity (R = -0.11). Our findings highlight genetic contributions to fitness, and the importance of the reproductively active individuals in a population to counteract loss of genetic variation in a wild, free-ranging social carnivore. It is crucial for managers to mitigate factors that significantly reduce effective population size and genetic connectivity, which supports the dispersion of genetic variation that aids in rapid evolutionary responses to environmental challenges.
Collapse
Affiliation(s)
- Bridgett M vonHoldt
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, United States
| | - Alexandra L DeCandia
- Department of Biology, Georgetown University, Washington, DC, United States
- Center for Conservation Genomics, Smithsonian’s National Zoo and Conservation Biology Institute, Washington, DC, United States
| | - Kira A Cassidy
- Yellowstone Center for Resources, Yellowstone National Park, WY, United States
| | - Erin E Stahler
- Yellowstone Center for Resources, Yellowstone National Park, WY, United States
| | - Janet S Sinsheimer
- Department of Biostatistics, Fielding School of Public Health, UCLA, Los Angeles, CA, United States
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, CA, United States
- Department of Computational Medicine, David Geffen School of Medicine, UCLA, Los Angeles, CA, United States
| | - Douglas W Smith
- Yellowstone Center for Resources, Yellowstone National Park, WY, United States
| | - Daniel R Stahler
- Yellowstone Center for Resources, Yellowstone National Park, WY, United States
| |
Collapse
|
123
|
Bredemeyer KR, vonHoldt BM, Foley NM, Childers IR, Brzeski KE, Murphy WJ. The value of hybrid genomes: Building two highly contiguous reference genome assemblies to advance Canis genomic studies. J Hered 2024; 115:480-486. [PMID: 38416051 DOI: 10.1093/jhered/esae013] [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: 01/02/2024] [Revised: 02/21/2024] [Accepted: 02/27/2024] [Indexed: 02/29/2024] Open
Abstract
Previous studies of canid population and evolutionary genetics have relied on high-quality domestic dog reference genomes that have been produced primarily for biomedical and trait mapping studies in dog breeds. However, the absence of highly contiguous genomes from other Canis species like the gray wolf and coyote, that represent additional distinct demographic histories, may bias inferences regarding interspecific genetic diversity and phylogenetic relationships. Here, we present single haplotype de novo genome assemblies for the gray wolf and coyote, generated by applying the trio-binning approach to long sequence reads generated from the genome of a female first-generation hybrid produced from a gray wolf and coyote mating. The assemblies were highly contiguous, with contig N50 sizes of 44.6 and 42.0 Mb for the wolf and coyote, respectively. Genome scaffolding and alignments between the two Canis assemblies and published dog reference genomes showed near complete collinearity, with one exception: a coyote-specific chromosome fission of chromosome 13 and fusion of the proximal portion of that chromosome with chromosome 8, retaining the Canis-typical haploid chromosome number of 2n = 78. We evaluated mapping quality for previous RADseq data from 334 canids and found nearly identical mapping quality and patterns among canid species and regional populations regardless of the genome used for alignment (dog, coyote, or gray wolf). These novel wolf and coyote genome reference assemblies will be important resources for proper and accurate inference of Canis demography, taxonomic evaluation, and conservation genetics.
Collapse
Affiliation(s)
- Kevin R Bredemeyer
- Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, United States
- Interdisciplinary Program in Genetics & Genomics, Texas A&M University, College Station, TX, United States
| | - Bridgett M vonHoldt
- Department of Ecology & Evolutionary Biology, Princeton University, Princeton, NJ, United States
| | - Nicole M Foley
- Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, United States
| | - Isabella R Childers
- Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, United States
- Interdisciplinary Program in Genetics & Genomics, Texas A&M University, College Station, TX, United States
| | - Kristin E Brzeski
- College of Forest Resources and Environment Science, Michigan Technological University, Houghton, MI, United States
| | - William J Murphy
- Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, United States
- Interdisciplinary Program in Genetics & Genomics, Texas A&M University, College Station, TX, United States
| |
Collapse
|
124
|
Burnham KL, Milind N, Lee W, Kwok AJ, Cano-Gamez K, Mi Y, Geoghegan CG, Zhang P, McKechnie S, Soranzo N, Hinds CJ, Knight JC, Davenport EE. eQTLs identify regulatory networks and drivers of variation in the individual response to sepsis. CELL GENOMICS 2024; 4:100587. [PMID: 38897207 PMCID: PMC11293594 DOI: 10.1016/j.xgen.2024.100587] [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: 11/07/2023] [Revised: 03/27/2024] [Accepted: 05/28/2024] [Indexed: 06/21/2024]
Abstract
Sepsis is a clinical syndrome of life-threatening organ dysfunction caused by a dysregulated response to infection, for which disease heterogeneity is a major obstacle to developing targeted treatments. We have previously identified gene-expression-based patient subgroups (sepsis response signatures [SRS]) informative for outcome and underlying pathophysiology. Here, we aimed to investigate the role of genetic variation in determining the host transcriptomic response and to delineate regulatory networks underlying SRS. Using genotyping and RNA-sequencing data on 638 adult sepsis patients, we report 16,049 independent expression (eQTLs) and 32 co-expression module (modQTLs) quantitative trait loci in this disease context. We identified significant interactions between SRS and genotype for 1,578 SNP-gene pairs and combined transcription factor (TF) binding site information (SNP2TFBS) and predicted regulon activity (DoRothEA) to identify candidate upstream regulators. Overall, these approaches identified putative mechanistic links between host genetic variation, cell subtypes, and the individual transcriptomic response to infection.
Collapse
Affiliation(s)
- Katie L Burnham
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Nikhil Milind
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK; University of Cambridge, Cambridge, UK
| | - Wanseon Lee
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Andrew J Kwok
- Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Kiki Cano-Gamez
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK; Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Yuxin Mi
- Centre for Human Genetics, University of Oxford, Oxford, UK
| | | | - Ping Zhang
- Centre for Human Genetics, University of Oxford, Oxford, UK; Chinese Academy of Medical Science Oxford Institute, University of Oxford, Oxford, UK
| | | | - Nicole Soranzo
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Charles J Hinds
- Centre for Translational Medicine & Therapeutics, William Harvey Research Institute, Faculty of Medicine & Dentistry, Queen Mary University of London, London, UK
| | - Julian C Knight
- Centre for Human Genetics, University of Oxford, Oxford, UK; Chinese Academy of Medical Science Oxford Institute, University of Oxford, Oxford, UK.
| | | |
Collapse
|
125
|
Dieckmann L, Lahti-Pulkkinen M, Cruceanu C, Räikkönen K, Binder EB, Czamara D. Quantitative trait locus mapping in placenta: A comparative study of chorionic villus and birth placenta. HGG ADVANCES 2024; 5:100326. [PMID: 38993113 DOI: 10.1016/j.xhgg.2024.100326] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Revised: 07/08/2024] [Accepted: 07/08/2024] [Indexed: 07/13/2024] Open
Abstract
The placenta, a pivotal player in the prenatal environment, holds crucial insights into early developmental pathways and future health outcomes. In this study, we explored genetic molecular regulation in chorionic villus samples (CVS) from the first trimester and placenta tissue at birth. We assessed quantitative trait locus (QTL) mapping on DNA methylation and gene expression data in a Finnish cohort of 574 individuals. We found more QTLs in birth placenta than in first-trimester placenta. Nevertheless, a substantial amount of associations overlapped in their effects and showed consistent direction in both tissues, with increasing molecular genetic effects from early pregnancy to birth placenta. The identified QTLs in birth placenta were most enriched in genes with placenta-specific expression. Conducting a phenome-wide-association study (PheWAS) on the associated SNPs, we observed numerous overlaps with genome-wide association study (GWAS) hits (spanning 57 distinct traits and 23 SNPs), with notable enrichments for immunological, skeletal, and respiratory traits. The QTL-SNP rs1737028 (chr6:29737993) presented with the highest number of GWAS hits. This SNP was related to HLA-G expression via DNA methylation and was associated with various immune, respiratory, and psychiatric traits. Our findings implicate increasing genetic molecular regulation during the course of pregnancy and support the involvement of placenta gene regulation, particularly in immunological traits. This study presents a framework for understanding placenta-specific gene regulation during pregnancy and its connection to health-related traits.
Collapse
Affiliation(s)
- Linda Dieckmann
- Department Genes and Environment, Max Planck Institute of Psychiatry, 80804 Munich, Germany; International Max Planck Research School for Translational Psychiatry, 80804 Munich, Germany
| | - Marius Lahti-Pulkkinen
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, 00014 Helsinki, Finland; Finnish Institute for Health and Welfare, 00271 Helsinki, Finland; Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh EH8 9YL, UK
| | - Cristiana Cruceanu
- Department of Physiology and Pharmacology, Karolinska Institute, 17177 Stockholm, Sweden
| | - Katri Räikkönen
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, 00014 Helsinki, Finland; Department of Obstetrics and Gynecology, Helsinki University Hospital, University of Helsinki, 00014 Helsinki, Finland
| | - Elisabeth B Binder
- Department Genes and Environment, Max Planck Institute of Psychiatry, 80804 Munich, Germany; Department of Psychiatry and Behavioral Sciences, School of Medicine, Emory University, Atlanta, GA 30322, USA.
| | - Darina Czamara
- Department Genes and Environment, Max Planck Institute of Psychiatry, 80804 Munich, Germany.
| |
Collapse
|
126
|
Rahimov F, Nieminen P, Kumari P, Juuri E, Nikopensius T, Paraiso K, German J, Karvanen A, Kals M, Elnahas AG, Karjalainen J, Kurki M, Palotie A, Heliövaara A, Esko T, Jukarainen S, Palta P, Ganna A, Patni AP, Mar D, Bomsztyk K, Mathieu J, Ruohola-Baker H, Visel A, Fakhouri WD, Schutte BC, Cornell RA, Rice DP. High incidence and geographic distribution of cleft palate cases in Finland are associated with a regulatory variant in IRF6. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.07.09.24310146. [PMID: 39040165 PMCID: PMC11261923 DOI: 10.1101/2024.07.09.24310146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/24/2024]
Abstract
In Finland the frequency of isolated cleft palate (CP) is higher than that of isolated cleft lip with or without cleft palate (CL/P). This trend contrasts to that in other European countries but its genetic underpinnings are unknown. We performed a genome-wide association study for orofacial clefts, which include CL/P and CP, in the Finnish population. We identified rs570516915, a single nucleotide polymorphism that is highly enriched in Finns and Estonians, as being strongly associated with CP ( P = 5.25 × 10 -34 , OR = 8.65, 95% CI 6.11-12.25), but not with CL/P ( P = 7.2 × 10 -5 ), with genome-wide significance. The risk allele frequency of rs570516915 parallels the regional variation of CP prevalence in Finland, and the association was replicated in independent cohorts of CP cases from Finland ( P = 8.82 × 10 -28 ) and Estonia ( P = 1.25 × 10 -5 ). The risk allele of rs570516915 disrupts a conserved binding site for the transcription factor IRF6 within a previously characterized enhancer upstream of the IRF6 gene. Through reporter assay experiments we found that the risk allele of rs570516915 diminishes the enhancer activity. Oral epithelial cells derived from CRISPR-Cas9 edited induced pluripotent stem cells demonstrate that the CP-associated allele of rs570516915 concomitantly decreases the binding of IRF6 and the expression level of IRF6 , suggesting impaired IRF6 autoregulation as a molecular mechanism underlying the risk for CP.
Collapse
|
127
|
Peris Sempere V, Luo G, Muñiz-Castrillo S, Pinto AL, Picard G, Rogemond V, Titulaer MJ, Finke C, Leypoldt F, Kuhlenbäumer G, Jones HF, Dale RC, Binks S, Irani SR, Bastiaansen AE, de Vries JM, de Bruijn MAAM, Roelen DL, Kim TJ, Chu K, Lee ST, Kanbayashi T, Pollock NR, Kichula KM, Mumme-Monheit A, Honnorat J, Norman PJ, Mignot E. HLA and KIR genetic association and NK cells in anti-NMDAR encephalitis. Front Immunol 2024; 15:1423149. [PMID: 39050850 PMCID: PMC11266021 DOI: 10.3389/fimmu.2024.1423149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2024] [Accepted: 06/06/2024] [Indexed: 07/27/2024] Open
Abstract
Introduction Genetic predisposition to autoimmune encephalitis with antibodies against N-methyl-D-aspartate receptor (NMDAR) is poorly understood. Given the diversity of associated environmental factors (tumors, infections), we hypothesized that human leukocyte antigen (HLA) and killer-cell immunoglobulin-like receptors (KIR), two extremely polymorphic gene complexes key to the immune system, might be relevant for the genetic predisposition to anti-NMDAR encephalitis. Notably, KIR are chiefly expressed by Natural Killer (NK) cells, recognize distinct HLA class I allotypes and play a major role in anti-tumor and anti-infection responses. Methods We conducted a Genome Wide Association Study (GWAS) with subsequent control-matching using Principal Component Analysis (PCA) and HLA imputation, in a multi-ethnic cohort of anti-NMDAR encephalitis (n=479); KIR and HLA were further sequenced in a large subsample (n=323). PCA-controlled logistic regression was then conducted for carrier frequencies (HLA and KIR) and copy number variation (KIR). HLA-KIR interaction associations were also modeled. Additionally, single cell sequencing was conducted in peripheral blood mononuclear cells from 16 cases and 16 controls, NK cells were sorted and phenotyped. Results Anti-NMDAR encephalitis showed a weak HLA association with DRB1*01:01~DQA1*01:01~DQB1*05:01 (OR=1.57, 1.51, 1.45; respectively), and DRB1*11:01 (OR=1.60); these effects were stronger in European descendants and in patients without an underlying ovarian teratoma. More interestingly, we found increased copy number variation of KIR2DL5B (OR=1.72), principally due to an overrepresentation of KIR2DL5B*00201. Further, we identified two allele associations in framework genes, KIR2DL4*00103 (25.4% vs. 12.5% in controls, OR=1.98) and KIR3DL3*00302 (5.3% vs. 1.3%, OR=4.44). Notably, the ligands of these KIR2DL4 and KIR3DL3, respectively, HLA-G and HHLA2, are known to act as immune checkpoint with immunosuppressive functions. However, we did not find differences in specific KIR-HLA ligand interactions or HLA-G polymorphisms between cases and controls. Similarly, gene expression of CD56dim or CD56bright NK cells did not differ between cases and controls. Discussion Our observations for the first time suggest that the HLA-KIR axis might be involved in anti-NMDAR encephalitis. While the genetic risk conferred by the identified polymorphisms appears small, a role of this axis in the pathophysiology of this disease appears highly plausible and should be analyzed in future studies.
Collapse
Affiliation(s)
- Vicente Peris Sempere
- Stanford Center for Sleep Science and Medicine, Stanford University, Palo Alto, CA, United States
| | - Guo Luo
- Stanford Center for Sleep Science and Medicine, Stanford University, Palo Alto, CA, United States
| | - Sergio Muñiz-Castrillo
- Stanford Center for Sleep Science and Medicine, Stanford University, Palo Alto, CA, United States
| | - Anne-Laurie Pinto
- French Reference Center on Paraneoplastic Neurological Syndrome and Autoimmune Encephalitis, Hospices Civils de Lyon, Lyon, France
- Institut MeLiS INSERM U1314/CNRS UMR 5284, Université Claude Bernard Lyon 1, Lyon, France
| | - Géraldine Picard
- French Reference Center on Paraneoplastic Neurological Syndrome and Autoimmune Encephalitis, Hospices Civils de Lyon, Lyon, France
- Institut MeLiS INSERM U1314/CNRS UMR 5284, Université Claude Bernard Lyon 1, Lyon, France
| | - Véronique Rogemond
- French Reference Center on Paraneoplastic Neurological Syndrome and Autoimmune Encephalitis, Hospices Civils de Lyon, Lyon, France
- Institut MeLiS INSERM U1314/CNRS UMR 5284, Université Claude Bernard Lyon 1, Lyon, France
| | | | - Carsten Finke
- Department of Neurology and Experimental Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Frank Leypoldt
- Department of Neurology, Christian-Albrechts-University/University Hospital Schleswig-Holstein, Kiel, Germany
- Neuroimmunology, Institute of Clinical Chemistry, University Hospital Schleswig-Holstein Kiel/Lübeck, Kiel, Germany
| | - Gregor Kuhlenbäumer
- Department of Neurology, Christian-Albrechts-University/University Hospital Schleswig-Holstein, Kiel, Germany
| | | | - Hannah F. Jones
- Starship Hospital, Centre for Brain Research, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand
| | - Russell C. Dale
- Kids Neuroscience Centre, Children’s Hospital at Westmead clinical school, University of Sydney, Sydney, NSW, Australia
| | - Sophie Binks
- Oxford Autoimmune Neurology Group, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- Department of Neurology, John Radcliffe Hospital, Oxford, United Kingdom
| | - Sarosh R. Irani
- Oxford Autoimmune Neurology Group, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- Departments of Neurology and Neurosciences, Mayo Clinic, Jacksonville, FL, United States
| | | | - Juna M. de Vries
- Department of Neurology, Erasmus Medical Center, Rotterdam, Netherlands
| | | | - Dave L. Roelen
- Department of Immunogenetics and Transplantation Immunology, Leiden University Medical Center, Leiden, Netherlands
| | - Tae-Joon Kim
- Department of Neurology, Ajou University School of Medicine, Suwon, Republic of Korea
| | - Kon Chu
- Department of Neurology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Soon-Tae Lee
- Department of Neurology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | | | - Nicholas R. Pollock
- Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO, United States
- Department of Immunology and Microbiology, University of Colorado School of Medicine, Aurora, CO, United States
| | - Katherine M. Kichula
- Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO, United States
- Department of Immunology and Microbiology, University of Colorado School of Medicine, Aurora, CO, United States
| | - Abigail Mumme-Monheit
- Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO, United States
- Department of Immunology and Microbiology, University of Colorado School of Medicine, Aurora, CO, United States
| | - Jérôme Honnorat
- French Reference Center on Paraneoplastic Neurological Syndrome and Autoimmune Encephalitis, Hospices Civils de Lyon, Lyon, France
- Institut MeLiS INSERM U1314/CNRS UMR 5284, Université Claude Bernard Lyon 1, Lyon, France
| | - Paul J. Norman
- Department of Biomedical Informatics, University of Colorado School of Medicine, Aurora, CO, United States
- Department of Immunology and Microbiology, University of Colorado School of Medicine, Aurora, CO, United States
| | - Emmanuel Mignot
- Stanford Center for Sleep Science and Medicine, Stanford University, Palo Alto, CA, United States
| |
Collapse
|
128
|
Venkatesh SS, Ganjgahi H, Palmer DS, Coley K, Linchangco GV, Hui Q, Wilson P, Ho YL, Cho K, Arumäe K, Wittemans LBL, Nellåker C, Vainik U, Sun YV, Holmes C, Lindgren CM, Nicholson G. Characterising the genetic architecture of changes in adiposity during adulthood using electronic health records. Nat Commun 2024; 15:5801. [PMID: 38987242 PMCID: PMC11237142 DOI: 10.1038/s41467-024-49998-0] [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: 01/25/2023] [Accepted: 06/25/2024] [Indexed: 07/12/2024] Open
Abstract
Obesity is a heritable disease, characterised by excess adiposity that is measured by body mass index (BMI). While over 1,000 genetic loci are associated with BMI, less is known about the genetic contribution to adiposity trajectories over adulthood. We derive adiposity-change phenotypes from 24.5 million primary-care health records in over 740,000 individuals in the UK Biobank, Million Veteran Program USA, and Estonian Biobank, to discover and validate the genetic architecture of adiposity trajectories. Using multiple BMI measurements over time increases power to identify genetic factors affecting baseline BMI by 14%. In the largest reported genome-wide study of adiposity-change in adulthood, we identify novel associations with BMI-change at six independent loci, including rs429358 (APOE missense variant). The SNP-based heritability of BMI-change (1.98%) is 9-fold lower than that of BMI. The modest genetic correlation between BMI-change and BMI (45.2%) indicates that genetic studies of longitudinal trajectories could uncover novel biology of quantitative traits in adulthood.
Collapse
Affiliation(s)
- Samvida S Venkatesh
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
| | - Habib Ganjgahi
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
- Department of Statistics, University of Oxford, Oxford, UK
| | - Duncan S Palmer
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
- Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Kayesha Coley
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Gregorio V Linchangco
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
- Atlanta VA Health Care System, Decatur, GA, USA
| | - Qin Hui
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
- Atlanta VA Health Care System, Decatur, GA, USA
| | - Peter Wilson
- Atlanta VA Health Care System, Decatur, GA, USA
- Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), Veterans Affairs Boston Healthcare System, Boston, MA, USA
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), Veterans Affairs Boston Healthcare System, Boston, MA, USA
- Division of Aging, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Kadri Arumäe
- Institute of Psychology, Faculty of Social Sciences, University of Tartu, Tartu, Estonia
| | - Laura B L Wittemans
- Novo Nordisk Research Centre Oxford, Oxford, UK
- Nuffield Department of Women's and Reproductive Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Christoffer Nellåker
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
- Nuffield Department of Women's and Reproductive Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Uku Vainik
- Institute of Psychology, Faculty of Social Sciences, University of Tartu, Tartu, Estonia
- Estonian Genome Centre, Institute of Genomics, Faculty of Science and Technology, University of Tartu, Tartu, Estonia
- Department of Neurology and Neurosurgery, Faculty of Medicine and Health Sciences, University of McGill, Montreal, Canada
| | - Yan V Sun
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
- Atlanta VA Health Care System, Decatur, GA, USA
| | - Chris Holmes
- Department of Statistics, University of Oxford, Oxford, UK
- Nuffield Department of Medicine, Medical Sciences Division, University of Oxford, Oxford, UK
- The Alan Turing Institute, London, UK
| | - Cecilia M Lindgren
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
- Nuffield Department of Women's and Reproductive Health, Medical Sciences Division, University of Oxford, Oxford, UK.
- Broad Institute of Harvard and MIT, Cambridge, MA, USA.
| | | |
Collapse
|
129
|
Lassen FH, Venkatesh SS, Baya N, Hill B, Zhou W, Bloemendal A, Neale BM, Kessler BM, Whiffin N, Lindgren CM, Palmer DS. Exome-wide evidence of compound heterozygous effects across common phenotypes in the UK Biobank. CELL GENOMICS 2024; 4:100602. [PMID: 38944039 PMCID: PMC11293579 DOI: 10.1016/j.xgen.2024.100602] [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: 07/31/2023] [Revised: 03/11/2024] [Accepted: 06/07/2024] [Indexed: 07/01/2024]
Abstract
The phenotypic impact of compound heterozygous (CH) variation has not been investigated at the population scale. We phased rare variants (MAF ∼0.001%) in the UK Biobank (UKBB) exome-sequencing data to characterize recessive effects in 175,587 individuals across 311 common diseases. A total of 6.5% of individuals carry putatively damaging CH variants, 90% of which are only identifiable upon phasing rare variants (MAF < 0.38%). We identify six recessive gene-trait associations (p < 1.68 × 10-7) after accounting for relatedness, polygenicity, nearby common variants, and rare variant burden. Of these, just one is discovered when considering homozygosity alone. Using longitudinal health records, we additionally identify and replicate a novel association between bi-allelic variation in ATP2C2 and an earlier age at onset of chronic obstructive pulmonary disease (COPD) (p < 3.58 × 10-8). Genetic phase contributes to disease risk for gene-trait pairs: ATP2C2-COPD (p = 0.000238), FLG-asthma (p = 0.00205), and USH2A-visual impairment (p = 0.0084). We demonstrate the power of phasing large-scale genetic cohorts to discover phenome-wide consequences of compound heterozygosity.
Collapse
Affiliation(s)
- Frederik H Lassen
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
| | - Samvida S Venkatesh
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Nikolas Baya
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Barney Hill
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Wei Zhou
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Analytical and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Alex Bloemendal
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Novo Nordisk Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Data Sciences Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Benjamin M Neale
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Analytical and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Benedikt M Kessler
- Target Discovery Institute, Centre for Medicines Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Nicola Whiffin
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Cecilia M Lindgren
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK; Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK; Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, UK.
| | - Duncan S Palmer
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK; Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA; Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, UK.
| |
Collapse
|
130
|
Sheu JJC, Lin WY, Liu TY, Chang CYY, Cheng J, Li YH, Chen CM, Tseng CC, Ding WY, Chung C, Hwang T, Chen PH, Tsai FJ. Ethnic-specific genetic susceptibility loci for endometriosis in Taiwanese-Han population: a genome-wide association study. J Hum Genet 2024:10.1038/s10038-024-01270-5. [PMID: 38982179 DOI: 10.1038/s10038-024-01270-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 06/18/2024] [Accepted: 06/23/2024] [Indexed: 07/11/2024]
Abstract
Endometriosis is a common gynecological disorder affecting around 10% of reproductive-age women. Although many hypotheses were proposed, genetic alteration has been considered as one of the key factors promoting pathogenesis. Due to racial/ethnic disparities in the process of hormone regulation and nutrition metabolism, a genome-wide association study (GWAS) with 2794 cases and 27,940 controls was conducted in a Taiwanese-Han population. Our study identified five significant susceptibility loci for endometriosis, and three of them, WNT4 (on the 1p36.12), RMND1 (6q25.1), and CCDC170 (6q25.1), have been previously associated with endometriosis across different populations, including European and Japanese descent cohorts. Other two including C5orf66/C5orf66-AS2 (5q31.1) and STN1 (10q24.33) are newly identified ones. Functional network analysis of potent risk genes revealed the involvement of cancer susceptibility and neurodevelopmental disorders in endometriosis development. In addition, long non-coding RNAs (lncRNAs) C5orf66 and C5orf66-AS2 can interact with many RNA-binding proteins (RBPs) which can influence RNA metabolic process, mRNA stabilization, and mRNA splicing, leading to dysregulation in tumor-promoting gene expression. Those findings support clinical observations of differences in the presentation of endometriosis in Taiwanese-Han population with higher risks of developing deeply infiltrating/invasive lesions and the associated malignancies.
Collapse
Affiliation(s)
- Jim Jinn-Chyuan Sheu
- Institute of Biomedical Sciences, National Sun Yatsen University, Kaohsiung, 804201, Taiwan
- Institute of Biopharmaceutical Sciences, National Sun Yatsen University, Kaohsiung, 804201, Taiwan
- Institute of Precision Medicine, National Sun Yatsen University, Kaohsiung, 804201, Taiwan
- School of Chinese Medicine, China Medical University, Taichung, 404333, Taiwan
- Department of Biotechnology, Kaohsiung Medical University, Kaohsiung, 807378, Taiwan
| | - Wei-Yong Lin
- Graduate Institute of Integrated Medicine, China Medical University, Taichung, 404333, Taiwan
- Department of Medical Research, China Medical University Hospital, Taichung, 404327, Taiwan
| | - Ting-Yuan Liu
- Department of Medical Research, China Medical University Hospital, Taichung, 404327, Taiwan
| | - Cherry Yin-Yi Chang
- Department of Obstetrics and Gynecology, China Medical University Hospital, Taichung, 404327, Taiwan
- Department of Medicine, School of Medicine, China Medical University, Taichung, 404333, Taiwan
| | - Jack Cheng
- Department of Medical Research, China Medical University Hospital, Taichung, 404327, Taiwan
| | - Yau-Hong Li
- Institute of Biomedical Sciences, National Sun Yatsen University, Kaohsiung, 804201, Taiwan
- Department of Obstetrics and Gynecology, Pingtung Veterans General Hospital, Pingtung, 900053, Taiwan
| | - Chih-Mei Chen
- Genetics Center, China Medical University Hospital, Taichung, 404327, Taiwan
| | - Chung-Chen Tseng
- Institute of Biomedical Sciences, National Sun Yatsen University, Kaohsiung, 804201, Taiwan
| | - Wendy Yarou Ding
- Genetics Center, China Medical University Hospital, Taichung, 404327, Taiwan
| | - Ching Chung
- Genetics Center, China Medical University Hospital, Taichung, 404327, Taiwan
| | - Tritium Hwang
- Institute of Biomedical Sciences, National Sun Yatsen University, Kaohsiung, 804201, Taiwan
| | - Ping-Ho Chen
- Institute of Biomedical Sciences, National Sun Yatsen University, Kaohsiung, 804201, Taiwan
- School of Dentistry, Kaohsiung Medical University, Kaohsiung, 807378, Taiwan
| | - Fuu-Jen Tsai
- School of Chinese Medicine, China Medical University, Taichung, 404333, Taiwan.
- Genetics Center, China Medical University Hospital, Taichung, 404327, Taiwan.
| |
Collapse
|
131
|
Lehrer S, Rheinstein PH. Tall women with breast cancer have poorer survival than short women. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.07.08.24310089. [PMID: 39040191 PMCID: PMC11261922 DOI: 10.1101/2024.07.08.24310089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/24/2024]
Abstract
Background Tall women are more likely to develop breast cancer (BC). High Mobility Group AT-Hook 1(HMGA1), an oncofetal protein, plays a role in the progression of breast cancer. Non-coding sequences proximal to HMGA1 contain variants associated with 4.83 cm taller height. In the current study, we used UK Biobank data to examine the relationship of HMGA1 to height, risk, and prognosis of women with breast cancer. Methods Our analysis included all subjects with invasive BC that occurred either before or after participant enrollment and were recorded in the UK Biobank database using self-reported data and the International Classification of Diseases (ICD10, ICD9). We divided the subjects into three previously described three height groups: Short (< 155 cm), Medium (155 cm to 175 cm), Tall (> 175 cm). We analyzed the HMGA1 SNP rs41269028, a single nucleotide intron variant, C > T, minor allele frequency 0.044. SNP rs41269028 was previously evaluated in subjects with diabetes. Results Height of 9583 women with BC homozygous for the HMGA1 SNP rs41269028 major allele was 162.29 cm ± 6.18. Height of 944 women with BC who were carriers or homozygotes (CT + TT) of the minor allele T was 162.88 cm ± 6.001. This difference was significant (p = 0.005). The effect of height group on survival was significant (p = 0.032, log rank test). Tall women had the poorest survival. The effect of HMGA1 SNP rs41269028 genotype on BC risk (p = 0.602) and survival (p = 0.439, log rank test) was insignificant. Conclusion We conclude that HMGA1 influences height, but we were unable to demonstrate that HMGA1 is related to increased incidence or poor prognosis of tall women with breast cancer. We did find that tall women with breast cancer have poorer survival than short women. Our finding that tall women have a worse prognosis is important because it could help the oncologist decide, along with other prognostic factors, whether adjuvant therapy is warranted.
Collapse
Affiliation(s)
- Steven Lehrer
- Department of Radiation Oncology, Icahn School of Medicine at Mount Sinai, New York
| | | |
Collapse
|
132
|
Hale MC, Pearse DE, Campbell MA. Characterization and distribution of a 14-Mb chromosomal inversion in native populations of rainbow trout (Oncorhynchus mykiss). G3 (BETHESDA, MD.) 2024; 14:jkae100. [PMID: 38885060 PMCID: PMC11228831 DOI: 10.1093/g3journal/jkae100] [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: 03/22/2024] [Accepted: 05/10/2024] [Indexed: 06/20/2024]
Abstract
Multiple studies in a range of taxa have found links between structural variants and the development of ecologically important traits. Such variants are becoming easier to find due, in large part, to the increase in the amount of genome-wide sequence data in nonmodel organisms. The salmonids (salmon, trout, and charr) are a taxonomic group with abundant genome-wide datasets due to their importance in aquaculture, fisheries, and variation in multiple ecologically important life-history traits. Previous research on rainbow trout (Oncorhynchus mykiss) has documented a large pericentric (∼55 Mb) chromosomal inversion (CI) on chromosome 5 (Omy05) and a second smaller (∼14 Mb) chromosome inversion on Omy20. While the Omy05 inversion appears to be associated with multiple adaptive traits, the inversion on Omy20 has received far less attention. In this study, we re-analyze RAD-seq and amplicon data from several populations of rainbow trout (O. mykiss) to better document the structure and geographic distribution of variation in the Omy20 CI. Moreover, we utilize phylogenomic techniques to characterize both the age- and the protein-coding gene content of the Omy20 CI. We find that the age of the Omy20 inversion dates to the early stages of O. mykiss speciation and predates the Omy05 inversion by ∼450,000 years. The 2 CIs differ further in terms of the frequency of the homokaryotypes. While both forms of the Omy05 CI are found across the eastern Pacific, the ancestral version of the Omy20 CI is restricted to the southern portion of the species range in California. Furthermore, the Omy20 inverted haplotype is comparable in genetic diversity to the ancestral form, whereas derived CIs typically show substantially reduced genetic diversity. These data contribute to our understanding of the age and distribution of a large CI in rainbow trout and provide a framework for researchers looking to document CIs in other nonmodel species.
Collapse
Affiliation(s)
- Matthew C Hale
- Department of Biology, Texas Christian University, Fort Worth, TX 76109, USA
| | - Devon E Pearse
- Southwest Fisheries Science Center, National Oceanic and Atmospheric Administration, Santa Cruz, CA 95064, USA
| | - Matthew A Campbell
- Department of Animal Science, University of California Davis, Davis, CA 95616, USA
| |
Collapse
|
133
|
Ibañez K, Jadhav B, Zanovello M, Gagliardi D, Clarkson C, Facchini S, Garg P, Martin-Trujillo A, Gies SJ, Deforie VG, Dalmia A, Hensman Moss DJ, Vandrovcova J, Rocca C, Moutsianas L, Marini-Bettolo C, Walker H, Turner C, Shoai M, Long JD, Fratta P, Langbehn DR, Tabrizi SJ, Caulfield MJ, Cortese A, Escott-Price V, Hardy J, Houlden H, Sharp AJ, Tucci A. Increased frequency of repeat expansion mutations across different populations. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.07.03.23292162. [PMID: 37461547 PMCID: PMC10350132 DOI: 10.1101/2023.07.03.23292162] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/25/2023]
Abstract
Repeat expansion disorders (REDs) are a devastating group of predominantly neurological diseases. Together they are common, affecting 1 in 3,000 people worldwide with population-specific differences. However, prevalence estimates of REDs are hampered by heterogeneous clinical presentation, variable geographic distributions, and technological limitations leading to under-ascertainment. Here, leveraging whole genome sequencing data from 82,176 individuals from different populations, we found an overall disease allele frequency of REDs of 1 in 283 individuals. Modelling disease prevalence using genetic data, age at onset and survival, we show that the expected number of people with REDs would be two to three times higher than currently reported figures, indicating under-diagnosis and/or incomplete penetrance. While some REDs are population-specific, e.g. Huntington disease-like 2 in Africans, most REDs are represented in all broad genetic ancestries (i.e. Europeans, Africans, Americans, East Asians, and South Asians), challenging the notion that some REDs are found only in specific populations. These results have worldwide implications for local and global health communities in the diagnosis and counselling of REDs.
Collapse
Affiliation(s)
- Kristina Ibañez
- William Harvey Research Institute, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Bharati Jadhav
- Department of Genetics and Genomic Sciences and Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
| | - Matteo Zanovello
- Department of Neuromuscular Diseases, Institute of Neurology, UCL, London, UK
| | - Delia Gagliardi
- William Harvey Research Institute, Queen Mary University of London, London, EC1M 6BQ, UK
- Department of Neuromuscular Diseases, Institute of Neurology, UCL, London, UK
| | - Christopher Clarkson
- William Harvey Research Institute, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Stefano Facchini
- Department of Neuromuscular Diseases, Institute of Neurology, UCL, London, UK
- IRCCS Mondino Foundation, Pavia, Italy
| | - Paras Garg
- Department of Genetics and Genomic Sciences and Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
| | - Alejandro Martin-Trujillo
- Department of Genetics and Genomic Sciences and Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
| | - Scott J Gies
- Department of Genetics and Genomic Sciences and Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
| | | | | | - Davina J. Hensman Moss
- St George’s, University of London, London, SW17 0RE, UK
- Department of Neurodegenerative Disorders, Queen Square Institute of Neurology, UCL, London, UK
| | - Jana Vandrovcova
- Department of Neuromuscular Diseases, Institute of Neurology, UCL, London, UK
| | - Clarissa Rocca
- Department of Neuromuscular Diseases, Institute of Neurology, UCL, London, UK
| | | | - Chiara Marini-Bettolo
- The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Helen Walker
- The John Walton Muscular Dystrophy Research Centre, Translational and Clinical Research Institute, Newcastle University and Newcastle Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK
| | - Chris Turner
- MRC Centre for Neuromuscular Disease, National Hospital for Neurology and Neurosurgery, Queen Square, London, WC1N 3BG
| | - Maryam Shoai
- Department of Neurodegenerative Disorders, Queen Square Institute of Neurology, UCL, London, UK
| | - Jeffrey D Long
- Departments of Psychiatry and Biostatistics, The University of Iowa, Iowa City, IA 52242, USA
| | | | - Pietro Fratta
- Department of Neuromuscular Diseases, Institute of Neurology, UCL, London, UK
| | - Douglas R Langbehn
- Departments of Psychiatry and Biostatistics, The University of Iowa, Iowa City, IA 52242, USA
| | - Sarah J Tabrizi
- UK Dementia Research Institute, UCL, London, UK
- Department of Neurodegenerative Disorders, Queen Square Institute of Neurology, UCL, London, UK
- Huntington’s Disease Centre, UCL, London, UK
| | - Mark J Caulfield
- William Harvey Research Institute, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Andrea Cortese
- Department of Neuromuscular Diseases, Institute of Neurology, UCL, London, UK
| | - Valentina Escott-Price
- Department of Psychological Medicine and Clinical Neuroscience, School of Medicine, Cardiff University, UK
- Dementia Research Institute, Cardiff University, UK
| | - John Hardy
- Department of Neurodegenerative Disorders, Queen Square Institute of Neurology, UCL, London, UK
| | - Henry Houlden
- Department of Neurodegenerative Disorders, Queen Square Institute of Neurology, UCL, London, UK
- Neurogenetics Unit, National Hospital for Neurology and Neurosurgery, London, UK
| | - Andrew J Sharp
- Department of Genetics and Genomic Sciences and Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
| | - Arianna Tucci
- William Harvey Research Institute, Queen Mary University of London, London, EC1M 6BQ, UK
- Department of Neuromuscular Diseases, Institute of Neurology, UCL, London, UK
| |
Collapse
|
134
|
Zhao J, O'Hagan A, Salter-Townshend M. How group structure impacts the numbers at risk for coronary artery disease: polygenic risk scores and nongenetic risk factors in the UK Biobank cohort. Genetics 2024; 227:iyae086. [PMID: 38781512 DOI: 10.1093/genetics/iyae086] [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: 03/22/2024] [Revised: 03/22/2024] [Accepted: 05/08/2024] [Indexed: 05/25/2024] Open
Abstract
The UK Biobank (UKB) is a large cohort study that recruited over 500,000 British participants aged 40-69 in 2006-2010 at 22 assessment centers from across the United Kingdom. Self-reported health outcomes and hospital admission data are 2 types of records that include participants' disease status. Coronary artery disease (CAD) is the most common cause of death in the UKB cohort. After distinguishing between prevalence and incidence CAD events for all UKB participants, we identified geographical variations in age-standardized rates of CAD between assessment centers. Significant distributional differences were found between the pooled cohort equation scores of UKB participants from England and Scotland using the Mann-Whitney test. Polygenic risk scores of UKB participants from England and Scotland and from different assessment centers differed significantly using permutation tests. Our aim was to discriminate between assessment centers with different disease rates by collecting data on disease-related risk factors. However, relying solely on individual-level predictions and averaging them to obtain group-level predictions proved ineffective, particularly due to the presence of correlated covariates resulting from participation bias. By using the Mundlak model, which estimates a random effects regression by including the group means of the independent variables in the model, we effectively addressed these issues. In addition, we designed a simulation experiment to demonstrate the functionality of the Mundlak model. Our findings have applications in public health funding and strategy, as our approach can be used to predict case rates in the future, as both population structure and lifestyle changes are uncertain.
Collapse
Affiliation(s)
- Jinbo Zhao
- Insight Centre for Data Analytics, University College Dublin, Belfield, Dublin D04V1W8, Ireland
- School of Mathematics and Statistics, University College Dublin, Belfield, Dublin D04V1W8, Ireland
| | - Adrian O'Hagan
- Insight Centre for Data Analytics, University College Dublin, Belfield, Dublin D04V1W8, Ireland
- School of Mathematics and Statistics, University College Dublin, Belfield, Dublin D04V1W8, Ireland
| | - Michael Salter-Townshend
- School of Mathematics and Statistics, University College Dublin, Belfield, Dublin D04V1W8, Ireland
| |
Collapse
|
135
|
Wiener E, Cottino L, Botha G, Nyangiri O, Noyes H, McLeod A, Jakubosky D, Adebamowo C, Awadalla P, Landouré G, Matshaba M, Matovu E, Ramsay M, Simo G, Simuunza M, Tiemessen C, Wonkam A, Sahibdeen V, Krause A, Lombard Z, Hazelhurst S. An assessment of the genomic structural variation landscape in Sub-Saharan African populations. RESEARCH SQUARE 2024:rs.3.rs-4485126. [PMID: 39041024 PMCID: PMC11261963 DOI: 10.21203/rs.3.rs-4485126/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/24/2024]
Abstract
Structural variants are responsible for a large part of genomic variation between individuals and play a role in both common and rare diseases. Databases cataloguing structural variants notably do not represent the full spectrum of global diversity, particularly missing information from most African populations. To address this representation gap, we analysed 1,091 high-coverage African genomes, 545 of which are public data sets, and 546 which have been analysed for structural variants for the first time. Variants were called using five different tools and datasets merged and jointly called using SURVIVOR. We identified 67,795 structural variants throughout the genome, with 10,421 genes having at least one variant. Using a conservative overlap in merged data, 6,414 of the structural variants (9.5%) are novel compared to the Database of Genomic Variants. This study contributes to knowledge of the landscape of structural variant diversity in Africa and presents a reliable dataset for potential applications in population genetics and health-related research.
Collapse
Affiliation(s)
- Emma Wiener
- Sydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Johannesburg, South Africa
- Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Laura Cottino
- Sydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Johannesburg, South Africa
- Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Gerrit Botha
- Computational Biology Unit, University of Cape Town, Cape Town, South Africa
| | - Oscar Nyangiri
- College of Veterinary Medicine, Animal Resources and Biosecurity Makerere University, Kampala, Uganda
| | - Harry Noyes
- Centre for Genomic Research, University of Liverpool, Liverpool, United Kingdom
| | - Annette McLeod
- Institute of Biodiversity, Animal Health and Comparative Medicine, University of Glasgow, Glasgow, United Kingdom
| | - David Jakubosky
- Department of Biomedical Informatics, University of California, San Diego, United States of America
- Institute of Genomic Medicine, University of California, San Diego, United States of America
| | - Clement Adebamowo
- Department of Epidemiology and Public Health and Greenebaum Comprehensive Cancer Center University of Maryland School of Medicine, Baltimore, United States of America
| | - Phillip Awadalla
- Ontario Institute for Cancer Research, Toronto, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Guida Landouré
- Faculty of Medicine and Odontostomatology University of Sciences, Techniques and Technology of Bamako, Bamako Mali
- Neurology Department Point ”G” University Hospital, Bamako, Mali
| | - Mogomotsi Matshaba
- Botswana-Baylor Children’s Clinical Center of Excellence, Gaborone, Botswana
- Baylor College of Medicine, Houston, United States
| | - Enock Matovu
- College of Veterinary Medicine, Animal Resources and Biosecurity Makerere University, Kampala, Uganda
| | - Michèle Ramsay
- Sydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Johannesburg, South Africa
| | - Gustave Simo
- Molecular Parasitology and Entomology Unit, Department of Biochemistry University of Dschang, Dschang, Cameroon
| | - Martin Simuunza
- Department of Disease Control, School of Veterinary Medicine University of Zambia, Lusaka, Zambia
| | - Caroline Tiemessen
- Centre for HIV and STIs, National Institute for Communicable Diseases, National Health Laboratory Services and Faculty of Health Sciences University of the Witwatersrand, Johannesburg, South Africa
| | - Ambroise Wonkam
- McKusick-Nathans Institute and Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, United States of America
- Division of Human Genetics, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
| | - Venesa Sahibdeen
- Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Amanda Krause
- Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Zané Lombard
- Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Scott Hazelhurst
- Sydney Brenner Institute for Molecular Bioscience, University of the Witwatersrand, Johannesburg, South Africa
- School of Electrical & Information Engineering, University of the Witwatersrand, Johannesburg, South Africa
| | | |
Collapse
|
136
|
Ghimire P, Palacios C, Trimble J, Lamichhaney S. Museum genomics approach to study the taxonomy and evolution of Woolly-necked storks using historic specimens. G3 (BETHESDA, MD.) 2024; 14:jkae081. [PMID: 38626302 DOI: 10.1093/g3journal/jkae081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 03/16/2024] [Accepted: 04/05/2024] [Indexed: 04/18/2024]
Abstract
The accessibility of genomic tools in evolutionary biology has allowed for a thorough exploration of various evolutionary processes associated with adaptation and speciation. However, genomic studies in natural systems present numerous challenges, reflecting the inherent complexities of studying organisms in their native habitats. The utilization of museum specimens for genomics research has received increased attention in recent times, facilitated by advancements in ancient DNA techniques. In this study, we have utilized a museum genomics approach to analyze historic specimens of Woolly-necked storks (Ciconia spp.) and examine their genetic composition and taxonomic status and explore the evolutionary and adaptive trajectories of populations over the years. The Woolly-necked storks are distributed in Asia and Africa with a taxonomic classification that has been a matter of ambiguity. Asian and African Woollynecks were recently recognized as different species based on their morphological differences; however, their genomic validation was lacking. In this study, we have used ∼70-year-old museum samples for whole-genome population-scale sequencing. Our study has revealed that Asian and African Woollynecks are genetically distinct, consistent with the current taxonomic classification based on morphological features. However, we also found a high genetic divergence between the Asian subspecies Ciconia episcopus neglecta and Ciconia episcopus episcopus, suggesting this classification requires a detailed examination to explore processes of ongoing speciation. Because taxonomic classification directly impacts conservation efforts, and there is evidence of declining populations of Asian Woollynecks in Southeast Asia, our results highlight that population-scale studies are urgent to determine the genetic, ecological, and phylogenetic diversity of these birds.
Collapse
Affiliation(s)
- Prashant Ghimire
- Department of Biological Sciences, Kent State University, Kent, OH 44240, USA
| | - Catalina Palacios
- Department of Biological Sciences, Kent State University, Kent, OH 44240, USA
| | - Jeremiah Trimble
- Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138, USA
| | - Sangeet Lamichhaney
- Department of Biological Sciences, Kent State University, Kent, OH 44240, USA
- School of Biomedical Sciences, Kent State University, Kent, OH 44240, USA
| |
Collapse
|
137
|
Casares-Marfil D, Martínez-Bueno M, Borghi MO, Pons-Estel G, Reales G, Zuo Y, Espinosa G, Radstake T, van den Hoogen LL, Wallace C, Guthridge J, James JA, Cervera R, Meroni PL, Martin J, Knight JS, Alarcón-Riquelme ME, Sawalha AH. A Genome-Wide Association Study Suggests New Susceptibility Loci for Primary Antiphospholipid Syndrome. Arthritis Rheumatol 2024. [PMID: 38973605 DOI: 10.1002/art.42947] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Revised: 05/13/2024] [Accepted: 06/20/2024] [Indexed: 07/09/2024]
Abstract
OBJECTIVE Primary antiphospholipid syndrome (PAPS) is a rare autoimmune disease characterized by the presence of antiphospholipid antibodies and the occurrence of thrombotic events and pregnancy complications. Our study aimed to identify novel genetic susceptibility loci associated with PAPS. METHODS We performed a genome-wide association study comprising 5,485 individuals (482 affected individuals) of European ancestry. Significant and suggestive independent variants from a meta-analysis of approximately 7 million variants were evaluated for functional and biological process enrichment. The genetic risk variability for PAPS in different populations was also assessed. Hierarchical clustering, Mahalanobis distance, and Dirichlet Process Mixtures with uncertainty clustering methods were used to assess genetic similarities between PAPS and other immune-mediated diseases. RESULTS We revealed genetic associations with PAPS in a regulatory locus within the HLA class II region near HLA-DRA and in STAT1-STAT4 with a genome-wide level of significance; 34 additional suggestive genetic susceptibility loci for PAPS were also identified. The disease risk allele near HLA-DRA is associated with overexpression of HLA-DRB6, HLA-DRB9, HLA-DQA2, and HLA-DQB2 in immune cells, vascular tissue, and nervous tissue. This association is independent of the association between PAPS and HLA-DRB1*1302. Functional analyses highlighted immune-related pathways in PAPS-associated loci. The comparison with other immune-mediated diseases revealed a close genetic relatedness to neuromyelitis optica, systemic sclerosis, and Sjögren syndrome, suggesting co-localized causal variations close to STAT1-STAT4, TNPO3, and BLK. CONCLUSION This study represents a comprehensive large-scale genetic analysis for PAPS and provides new insights into the genetic basis and pathophysiology of this rare disease.
Collapse
Affiliation(s)
| | | | | | | | | | - Yu Zuo
- University of Michigan, Ann Arbor
| | | | | | | | | | | | | | | | | | - Javier Martin
- Institute of Parastitology and Biomedicine López-Neyra, Spanish National Research Council, Granada, Spain
| | | | | | | |
Collapse
|
138
|
Vega-Retter C, Rojas-Hernández N, Cortés-Miranda J, Véliz D, Rico C. Genome scans reveal signals of selection associated with pollution in fish populations of Basilichthys microlepidotus, an endemic species of Chile. Sci Rep 2024; 14:15727. [PMID: 38977738 PMCID: PMC11231317 DOI: 10.1038/s41598-024-66121-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] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Accepted: 06/27/2024] [Indexed: 07/10/2024] Open
Abstract
The Maipo River catchment is one of Chile's most polluted basins. In recent decades, discharges of untreated sewage and organic matter have caused eutrophication and water quality degradation. We employed the indigenous silverfish species Basilichthys microlepidotus as a model organism to investigate the process of adaptation and selection on genes influenced by pollution. Using variation at single nucleotide polymorphisms (SNPs), we determined the temporal stability of the population structure patterns previously identified in this species by varying SNPs. We also examined local adaptation to pollution-selected genes. Using the genotypes of 7684 loci in 180 individuals, we identified 429 and 700 loci that may be undergoing selection. We detected these loci using the FSTHET and ARLEQUIN outlier detection software, respectively. Both software packages simultaneously identified a total of 250 loci. B. microlepidotus' population structure did not change over time at contaminated or unpolluted sites. In addition, our analysis found: (i) selection of genes associated with pollution, consistent with observations in other organisms; (ii) identification of candidate genes that are functionally linked to the same biological processes, molecular functions and/or cellular components that previously showed differential expression in the same populations; and (iii) a candidate gene with differential expression and a non-synonymous substitution.
Collapse
Affiliation(s)
- Caren Vega-Retter
- Departamento de Ciencias Ecológicas, Facultad de Ciencias, Universidad de Chile, Las Palmeras #3425, Ñuñoa, Santiago, Chile
| | - Noemi Rojas-Hernández
- Departamento de Ciencias Ecológicas, Facultad de Ciencias, Universidad de Chile, Las Palmeras #3425, Ñuñoa, Santiago, Chile
| | - Jorge Cortés-Miranda
- Departamento de Ciencias Ecológicas, Facultad de Ciencias, Universidad de Chile, Las Palmeras #3425, Ñuñoa, Santiago, Chile
| | - David Véliz
- Departamento de Ciencias Ecológicas, Facultad de Ciencias, Universidad de Chile, Las Palmeras #3425, Ñuñoa, Santiago, Chile
- Centro de Ecología y Manejo Sustentable de Islas Oceánicas (ESMOI), Coquimbo, Chile
| | - Ciro Rico
- Instituto de Ciencias Marinas de Andalucía (ICMAN), CSIC. Campus Universitario Río San Pedro, C. Republica Saharaui, 4, 11519, Puerto Real, Cádiz, Spain.
| |
Collapse
|
139
|
Kasyanov E, Pinakhina D, Rakitko A, Vergasova E, Yermakovich D, Rukavishnikov G, Malyshko L, Popov Y, Kovalenko E, Ilinskaya A, Kim A, Plotnikov N, Neznanov N, Ilinsky V, Kibitov A, Mazo G. Genetic Associations of Anhedonia: Insights into Overlap of Mental and Somatic Disorders. CONSORTIUM PSYCHIATRICUM 2024; 5:5-15. [PMID: 39072000 PMCID: PMC11272301 DOI: 10.17816/cp15494] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Accepted: 05/08/2024] [Indexed: 07/30/2024] Open
Abstract
BACKGROUND Anhedonia is characterized by a reduced ability to anticipate, experience, and/or learn about pleasure. This phenomenon has a transdiagnostic nature and is one of the key symptoms of mood disorders, schizophrenia, addictions, and somatic conditions. AIM To evaluate the genetic architecture of anhedonia and its overlap with other mental disorders and somatic conditions. METHODS We performed a genome-wide association study of anhedonia on a sample of 4,520 individuals from a Russian non-clinical population. Using the available summary statistics, we calculated polygenic risk scores (PRS) to investigate the genetic relationship between anhedonia and other psychiatric or somatic phenotypes. RESULTS No variants with a genome-wide significant association were identified. PRS for major depression, bipolar disorder, and schizophrenia were significantly associated with anhedonia. Conversely, no significant associations were found between PRS for anxiety and anhedonia, which aligns well with existing clinical evidence. None of the PRS for somatic phenotypes attained a significance level after correction for multiple comparisons. A nominal significance for the anhedonia association was determined for omega-3 fatty acids, type 2 diabetes mellitus, and Crohn's disease. CONCLUSION Anhedonia has a complex polygenic architecture, and its presence in somatic diseases or normal conditions may be due to a genetic predisposition to mood disorders or schizophrenia.
Collapse
|
140
|
Schönberger J, Steinhaus R, Seelow D. Drawing human pedigree charts with DrawPed. Nucleic Acids Res 2024; 52:W61-W64. [PMID: 38726873 PMCID: PMC11223805 DOI: 10.1093/nar/gkae336] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 03/29/2024] [Accepted: 04/19/2024] [Indexed: 07/06/2024] Open
Abstract
Creating pedigree charts is a recurring task in biomedical research, but there are few online tools for drawing complex human pedigrees available and even fewer are free. With DrawPed we aim to close this gap. DrawPed automatically draws pedigree charts from standard PED format pedigree files. Users can also create pedigrees from scratch and interactively edit existing pedigrees. The application can display conditions not captured in a PED file such as deceased persons or suspected consanguinity of parents. Pedigree charts are displayed as SVGs, which are scalable and hence publication-ready. Pedigrees can be exported as PED files for storage, exchange, or use in other applications. DrawPed is open source and freely available at https://www.genecascade.org/DrawPed/.
Collapse
Affiliation(s)
- Janina Schönberger
- Exploratory Diagnostic Sciences, Berliner Institut für Gesundheitsforschung@Charité, Charitéplatz 1, 10117, Berlin, Germany
- Institut für medizinische Genetik und Humangenetik, Charité – Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Robin Steinhaus
- Exploratory Diagnostic Sciences, Berliner Institut für Gesundheitsforschung@Charité, Charitéplatz 1, 10117, Berlin, Germany
- Institut für medizinische Genetik und Humangenetik, Charité – Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Dominik Seelow
- Exploratory Diagnostic Sciences, Berliner Institut für Gesundheitsforschung@Charité, Charitéplatz 1, 10117, Berlin, Germany
- Institut für medizinische Genetik und Humangenetik, Charité – Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| |
Collapse
|
141
|
Laghouaouta H, Laplana M, Ros-Freixedes R, Fraile LJ, Pena RN. Sequence variants associated with resilient responses in growing pigs. J Anim Breed Genet 2024. [PMID: 38967062 DOI: 10.1111/jbg.12886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 05/23/2024] [Accepted: 06/18/2024] [Indexed: 07/06/2024]
Abstract
The current work aimed to identify genomic regions and candidate genes associated with resilience in pigs. In previous work, we proposed the body weight deviation from the expected growth curve (ΔBW) and the increase of the positive acute-phase protein haptoglobin (ΔHP) after a vaccine challenge as resilience indicators which may be improved through selective breeding in pigs. Individuals with steady growth rate and minor activation of haptoglobin (high ΔBW and low ΔHP values) were considered resilient. In contrast, pigs with perturbed growth rate and high activation of haptoglobin (low ΔBW and high ΔHP values) were considered susceptible. Both ∆BW and ∆HP were simultaneously considered to select the most resilient (N = 40) and susceptible (N = 40) pigs. A genome-wide association study was carried out for the pigs' response classification to the challenge test using whole-genome sequence data (7,760,720 variants). Eleven associated genomic regions were identified, harbouring relevant candidate genes related to the immune response (such as pro- and anti-inflammatory responses) and growth pathways. These associated genomic regions harboured 41 potential functional mutations (frameshift, splice donor, splice acceptor, start loss and stop loss/gain) in candidate genes. Overall, this study advances our knowledge about the genetic determinism of resilience, highlighting its polygenic nature and strong relationship with immunity and growth.
Collapse
Affiliation(s)
- Houda Laghouaouta
- Department of Animal Science, University of Lleida-Agrotecnio-CERCA Center, Lleida, Spain
| | - Marina Laplana
- Department of Animal Science, University of Lleida-Agrotecnio-CERCA Center, Lleida, Spain
| | - Roger Ros-Freixedes
- Department of Animal Science, University of Lleida-Agrotecnio-CERCA Center, Lleida, Spain
| | - Lorenzo J Fraile
- Department of Animal Science, University of Lleida-Agrotecnio-CERCA Center, Lleida, Spain
| | - Ramona N Pena
- Department of Animal Science, University of Lleida-Agrotecnio-CERCA Center, Lleida, Spain
| |
Collapse
|
142
|
Forer L, Taliun D, LeFaive J, Smith AV, Boughton A, Coassin S, Lamina C, Kronenberg F, Fuchsberger C, Schönherr S. Imputation Server PGS: an automated approach to calculate polygenic risk scores on imputation servers. Nucleic Acids Res 2024; 52:W70-W77. [PMID: 38709879 PMCID: PMC11223871 DOI: 10.1093/nar/gkae331] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Revised: 04/02/2024] [Accepted: 04/15/2024] [Indexed: 05/08/2024] Open
Abstract
Polygenic scores (PGS) enable the prediction of genetic predisposition for a wide range of traits and diseases by calculating the weighted sum of allele dosages for genetic variants associated with the trait or disease in question. Present approaches for calculating PGS from genotypes are often inefficient and labor-intensive, limiting transferability into clinical applications. Here, we present 'Imputation Server PGS', an extension of the Michigan Imputation Server designed to automate a standardized calculation of polygenic scores based on imputed genotypes. This extends the widely used Michigan Imputation Server with new functionality, bringing the simplicity and efficiency of modern imputation to the PGS field. The service currently supports over 4489 published polygenic scores from publicly available repositories and provides extensive quality control, including ancestry estimation to report population stratification. An interactive report empowers users to screen and compare thousands of scores in a fast and intuitive way. Imputation Server PGS provides a user-friendly web service, facilitating the application of polygenic scores to a wide range of genetic studies and is freely available at https://imputationserver.sph.umich.edu.
Collapse
Affiliation(s)
- Lukas Forer
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Daniel Taliun
- Canada Excellence Research Chair in Genomic Medicine, McGill University, Montreal, Québec, Canada
- Department of Human Genetics, Faculty of Medicine and Health Sciences, McGill University, Montréal, Québec, Canada
| | - Jonathon LeFaive
- Department of Biostatistics and the Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Albert V Smith
- Department of Biostatistics and the Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Andrew P Boughton
- Department of Biostatistics and the Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Stefan Coassin
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Claudia Lamina
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| | - Christian Fuchsberger
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
- Department of Biostatistics and the Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109, USA
- Institute for Biomedicine, Eurac Research, Bolzano, Italy
| | - Sebastian Schönherr
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria
| |
Collapse
|
143
|
Meyermans R, Janssens S, Coussé A, Tinel S, Gorssen W, Lepot F, Hubin X, Mayeres P, Veulemans W, De Wilde N, Druet T, Georges M, Charlier C, Claerebout E, Buys N. Genetic and genomic analysis of Belgian Blue's susceptibility for psoroptic mange. Genet Sel Evol 2024; 56:52. [PMID: 38969989 PMCID: PMC11227209 DOI: 10.1186/s12711-024-00921-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2024] [Accepted: 07/01/2024] [Indexed: 07/07/2024] Open
Abstract
BACKGROUND Psoroptic mange, caused by Psoroptes ovis mites, is affecting Belgian Blue cattle's welfare and production potential. The Belgian Blue cattle-known for its high degree of muscling, low feed conversion ratio and high beef quality-is highly susceptible for this disease. RESULTS In this study, we phenotyped 1975 Belgian Blue cattle from more than 100 different groups on commercial beef farms for their psoroptic mange susceptibility. Substantial individual differences were observed within these management groups, with lesion extent differences up to ± 15%. Animal models showed that estimated heritabilities were low for lesion extent and severe lesion extent (0.07 and 0.09, respectively) and 0.12 for the number of mites. A genome wide association study for mange susceptibility revealed signals on BTA6, BTA11, BTA15 and BTA24. In these regions, candidate genes GBA3, RAG2, and TRAF6 were identified. CONCLUSIONS Despite the challenges in phenotyping for psoroptic mange due to the timing of screening, the continuous evolution of lesions and different management conditions, we successfully conducted a study on the genetic susceptibility to psoroptic mange in Belgian Blue cattle. Our results clearly indicate that psoroptic mange is under polygenic control and the underlying candidate genes should be studied more thoroughly. This is the first study providing candidate genes for this complex disease. These results are already valuable for Belgian Blue breeding, however, further research is needed to unravel the architecture of this disease and to identify causal mutations.
Collapse
Affiliation(s)
- Roel Meyermans
- Center for Animal Breeding and Genetics, Department of Biosystems, KU Leuven, 3001, Leuven, Belgium.
| | - Steven Janssens
- Center for Animal Breeding and Genetics, Department of Biosystems, KU Leuven, 3001, Leuven, Belgium
| | - Annelies Coussé
- Center for Animal Breeding and Genetics, Department of Biosystems, KU Leuven, 3001, Leuven, Belgium
| | - Susanne Tinel
- Center for Animal Breeding and Genetics, Department of Biosystems, KU Leuven, 3001, Leuven, Belgium
| | - Wim Gorssen
- Center for Animal Breeding and Genetics, Department of Biosystems, KU Leuven, 3001, Leuven, Belgium
| | | | | | | | | | - Nathalie De Wilde
- Department of Translational Physiology, Infectiology and Public Health, UGent, 9820, Merelbeke, Belgium
| | - Tom Druet
- Unit of Animal Genomics, GIGA Institute and Faculty of Veterinary Medicine, Liège University, 4000, Liège, Belgium
| | - Michel Georges
- Unit of Animal Genomics, GIGA Institute and Faculty of Veterinary Medicine, Liège University, 4000, Liège, Belgium
| | - Carole Charlier
- Unit of Animal Genomics, GIGA Institute and Faculty of Veterinary Medicine, Liège University, 4000, Liège, Belgium
| | - Edwin Claerebout
- Department of Translational Physiology, Infectiology and Public Health, UGent, 9820, Merelbeke, Belgium
| | - Nadine Buys
- Center for Animal Breeding and Genetics, Department of Biosystems, KU Leuven, 3001, Leuven, Belgium
| |
Collapse
|
144
|
Jacinto JGP, Letko A, Häfliger IM, Drögemüller C, Agerholm JS. Congenital syndromic Chiari-like malformation (CSCM) in Holstein cattle: towards unravelling of possible genetic causes. Acta Vet Scand 2024; 66:29. [PMID: 38965607 PMCID: PMC11229497 DOI: 10.1186/s13028-024-00752-y] [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: 04/18/2024] [Accepted: 07/01/2024] [Indexed: 07/06/2024] Open
Abstract
BACKGROUND Chiari malformation type II (CMII) was originally reported in humans as a rare disorder characterized by the downward herniation of the hindbrain and towering cerebellum. The congenital brain malformation is usually accompanied by spina bifida, a congenital spinal anomaly resulting from incomplete closure of the dorsal aspect of the spinal neural tube, and occasionally by other lesions. A similar disorder has been reported in several animal species, including cattle, particularly as a congenital syndrome. A cause of congenital syndromic Chiari-like malformation (CSCM) in cattle has not been reported to date. We collected a series of 14 CSCM-affected Holstein calves (13 purebred, one Red Danish Dairy F1 cross) and performed whole-genome sequencing (WGS). WGS was performed on 33 cattle, including eight cases with parents (trio-based; group 1), three cases with one parent (group 2), and three single cases (solo-based; group 3). RESULTS Sequencing-based genome-wide association study of the 13 Holstein calves with CSCM and 166 controls revealed no significantly associated genome region. Assuming a single Holstein breed-specific recessive allele, no region of shared homozygosity was detected suggesting heterogeneity. Subsequent filtering for protein-changing variants that were only homozygous in the genomes of the individual cases allowed the identification of two missense variants affecting different genes, SHC4 in case 4 in group 1 and WDR45B in case 13 in group 3. Furthermore, these two variants were only observed in Holstein cattle when querying WGS data of > 5,100 animals. Alternatively, potential de novo mutational events were assessed in each case. Filtering for heterozygous private protein-changing variants identified one DYNC1H1 frameshift variant as a candidate causal dominant acting allele in case 12 in group 3. Finally, the presence of larger structural DNA variants and chromosomal abnormalities was investigated in all cases. Depth of coverage analysis revealed two different partial monosomies of chromosome 2 segments in cases 1 and 7 in group 1 and a trisomy of chromosome 12 in the WDR45B homozygous case 13 in group 3. CONCLUSIONS This study presents for the first time a detailed genomic evaluation of CSCM in Holstein cattle and suggests an unexpected genetic and allelic heterogeneity considering the mode of inheritance, as well as the type of variant. For the first time, we propose candidate causal variants that may explain bovine CSCM in a certain proportion of affected calves. We present cattle as a large animal model for human CMII and propose new genes and genomic variants as possible causes for related diseases in both animals and humans.
Collapse
Affiliation(s)
- Joana Goncalves Pontes Jacinto
- Institute of Genetics, Vetsuisse Faculty, University of Bern, Bremgartenstrasse 109a, Bern, 3012, Switzerland
- Clinic for Ruminants, Vetsuisse Faculty, University of Bern, Bremgartenstrasse 109a, Bern, 3012, Switzerland
| | - Anna Letko
- Institute of Genetics, Vetsuisse Faculty, University of Bern, Bremgartenstrasse 109a, Bern, 3012, Switzerland
| | - Irene Monika Häfliger
- Institute of Genetics, Vetsuisse Faculty, University of Bern, Bremgartenstrasse 109a, Bern, 3012, Switzerland
| | - Cord Drögemüller
- Institute of Genetics, Vetsuisse Faculty, University of Bern, Bremgartenstrasse 109a, Bern, 3012, Switzerland.
| | - Jørgen Steen Agerholm
- Department of Veterinary Clinical Sciences, University of Copenhagen, Højbakkegaard Allé 5A, Taastrup, 2630, Denmark
| |
Collapse
|
145
|
Gao H, Wei L, Indulkar S, Nguyen TTL, Liu D, Ho MF, Zhang C, Li H, Weinshilboum RM, Ingle JN, Wang L. Androgen receptor-mediated pharmacogenomic expression quantitative trait loci: implications for breast cancer response to AR-targeting therapy. Breast Cancer Res 2024; 26:111. [PMID: 38965614 PMCID: PMC11225427 DOI: 10.1186/s13058-024-01861-2] [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: 11/17/2023] [Accepted: 06/20/2024] [Indexed: 07/06/2024] Open
Abstract
BACKGROUND Endocrine therapy is the most important treatment modality of breast cancer patients whose tumors express the estrogen receptor α (ERα). The androgen receptor (AR) is also expressed in the vast majority (80-90%) of ERα-positive tumors. AR-targeting drugs are not used in clinical practice, but have been evaluated in multiple trials and preclinical studies. METHODS We performed a genome-wide study to identify hormone/drug-induced single nucleotide polymorphism (SNP) genotype - dependent gene-expression, known as PGx-eQTL, mediated by either an AR agonist (dihydrotestosterone) or a partial antagonist (enzalutamide), utilizing a previously well characterized lymphoblastic cell line panel. The association of the identified SNPs-gene pairs with breast cancer phenotypes were then examined using three genome-wide association (GWAS) studies that we have published and other studies from the GWAS catalog. RESULTS We identified 13 DHT-mediated PGx-eQTL loci and 23 Enz-mediated PGx-eQTL loci that were associated with breast cancer outcomes post ER antagonist or aromatase inhibitors (AI) treatment, or with pharmacodynamic (PD) effects of AIs. An additional 30 loci were found to be associated with cancer risk and sex-hormone binding globulin levels. The top loci involved the genes IDH2 and TMEM9, the expression of which were suppressed by DHT in a PGx-eQTL SNP genotype-dependent manner. Both of these genes were overexpressed in breast cancer and were associated with a poorer prognosis. Therefore, suppression of these genes by AR agonists may benefit patients with minor allele genotypes for these SNPs. CONCLUSIONS We identified AR-related PGx-eQTL SNP-gene pairs that were associated with risks, outcomes and PD effects of endocrine therapy that may provide potential biomarkers for individualized treatment of breast cancer.
Collapse
Affiliation(s)
- Huanyao Gao
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, 200 First Street Southwest, Rochester, MN, 55905, USA
| | - Lixuan Wei
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, 200 First Street Southwest, Rochester, MN, 55905, USA
| | - Shreya Indulkar
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, 200 First Street Southwest, Rochester, MN, 55905, USA
| | - Thanh Thanh L Nguyen
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, 200 First Street Southwest, Rochester, MN, 55905, USA
| | - Duan Liu
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, 200 First Street Southwest, Rochester, MN, 55905, USA
| | - Ming-Fen Ho
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, 200 First Street Southwest, Rochester, MN, 55905, USA
| | - Cheng Zhang
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, 200 First Street Southwest, Rochester, MN, 55905, USA
| | - Hu Li
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, 200 First Street Southwest, Rochester, MN, 55905, USA
| | - Richard M Weinshilboum
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, 200 First Street Southwest, Rochester, MN, 55905, USA
| | - James N Ingle
- Department of Oncology, Mayo Clinic, Rochester, MN, USA
| | - Liewei Wang
- Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, 200 First Street Southwest, Rochester, MN, 55905, USA.
| |
Collapse
|
146
|
North HL, Fu Z, Metz R, Stull MA, Johnson CD, Shirley X, Crumley K, Reisig D, Kerns DL, Gilligan T, Walsh T, Jiggins CD, Sword GA. Rapid Adaptation and Interspecific Introgression in the North American Crop Pest Helicoverpa zea. Mol Biol Evol 2024; 41:msae129. [PMID: 38941083 PMCID: PMC11259193 DOI: 10.1093/molbev/msae129] [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: 09/19/2023] [Revised: 06/12/2024] [Accepted: 06/14/2024] [Indexed: 06/29/2024] Open
Abstract
Insect crop pests threaten global food security. This threat is amplified through the spread of nonnative species and through adaptation of native pests to control measures. Adaptations such as pesticide resistance can result from selection on variation within a population, or through gene flow from another population. We investigate these processes in an economically important noctuid crop pest, Helicoverpa zea, which has evolved resistance to a wide range of pesticides. Its sister species Helicoverpa armigera, first detected as an invasive species in Brazil in 2013, introduced the pyrethroid-resistance gene CYP337B3 to South American H. zea via adaptive introgression. To understand whether this could contribute to pesticide resistance in North America, we sequenced 237 H. zea genomes across 10 sample sites. We report H. armigera introgression into the North American H. zea population. Two individuals sampled in Texas in 2019 carry H. armigera haplotypes in a 4 Mbp region containing CYP337B3. Next, we identify signatures of selection in the panmictic population of nonadmixed H. zea, identifying a selective sweep at a second cytochrome P450 gene: CYP333B3. We estimate that its derived allele conferred a ∼5% fitness advantage and show that this estimate explains independently observed rare nonsynonymous CYP333B3 mutations approaching fixation over a ∼20-year period. We also detect putative signatures of selection at a kinesin gene associated with Bt resistance. Overall, we document two mechanisms of rapid adaptation: the introduction of fitness-enhancing alleles through interspecific introgression, and selection on intraspecific variation.
Collapse
Affiliation(s)
- Henry L North
- Department of Zoology, University of Cambridge, Cambridge CB2 3EJ, UK
| | - Zhen Fu
- Department of Entomology, Texas A&M University, College Station, TX 77843, USA
- Bioinformatics and Biostatistics Core, Van Andel Institute, Grand Rapids, MI 49503, USA
| | - Richard Metz
- AgriLife Genomics and Bioinformatics Service, Texas A&M University, College Station, TX 77843, USA
| | - Matt A Stull
- AgriLife Genomics and Bioinformatics Service, Texas A&M University, College Station, TX 77843, USA
| | - Charles D Johnson
- AgriLife Genomics and Bioinformatics Service, Texas A&M University, College Station, TX 77843, USA
| | - Xanthe Shirley
- Animal and Plant Health Inspection Service, United States Department of Agriculture, College Station, TX, USA
| | - Kate Crumley
- Agrilife Extension, Texas A&M University, Wharton, TX, USA
| | - Dominic Reisig
- Department of Entomology and Plant Pathology, North Carolina State University, Plymouth, NC, 27962, USA
| | - David L Kerns
- Department of Entomology, Texas A&M University, College Station, TX 77843, USA
| | - Todd Gilligan
- Animal and Plant Health Inspection Service, United States Department of Agriculture, Fort Collins, CO, USA
| | - Tom Walsh
- Black Mountain Laboratories, Commonwealth Scientific and Industrial Research Organization, Canberra, Australia
| | - Chris D Jiggins
- Department of Zoology, University of Cambridge, Cambridge CB2 3EJ, UK
| | - Gregory A Sword
- Department of Entomology, Texas A&M University, College Station, TX 77843, USA
| |
Collapse
|
147
|
Bougiouri K, Aninta SG, Charlton S, Harris A, Carmagnini A, Piličiauskienė G, Feuerborn TR, Scarsbrook L, Tabadda K, Blaževičius P, Parker HG, Gopalakrishnan S, Larson G, Ostrander EA, Irving-Pease EK, Frantz LA, Racimo F. Imputation of ancient canid genomes reveals inbreeding history over the past 10,000 years. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.15.585179. [PMID: 38903121 PMCID: PMC11188068 DOI: 10.1101/2024.03.15.585179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/22/2024]
Abstract
The multi-millenia long history between dogs and humans has placed them at the forefront of archeological and genomic research. Despite ongoing efforts including the analysis of ancient dog and wolf genomes, many questions remain regarding their geographic and temporal origins, and the microevolutionary processes that led to the diversity of breeds today. Although ancient genomes provide valuable information, their use is hindered by low depth of coverage and post-mortem damage, which inhibits confident genotype calling. In the present study, we assess how genotype imputation of ancient dog and wolf genomes, utilising a large reference panel, can improve the resolution provided by ancient datasets. Imputation accuracy was evaluated by down-sampling high coverage dog and wolf genomes to 0.05-2x coverage and comparing concordance between imputed and high coverage genotypes. We measured the impact of imputation on principal component analyses and runs of homozygosity. Our findings show high (R2>0.9) imputation accuracy for dogs with coverage as low as 0.5x and for wolves as low as 1.0x. We then imputed a dataset of 90 ancient dog and wolf genomes, to assess changes in inbreeding during the last 10,000 years of dog evolution. Ancient dog and wolf populations generally exhibited lower inbreeding levels than present-day individuals. Interestingly, regions with low ROH density maintained across ancient and present-day samples were significantly associated with genes related to olfaction and immune response. Our study indicates that imputing ancient canine genomes is a viable strategy that allows for the use of analytical methods previously limited to high-quality genetic data.
Collapse
Affiliation(s)
- Katia Bougiouri
- Section for Molecular Ecology and Evolution, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Sabhrina Gita Aninta
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK
- Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Sophy Charlton
- BioArCh, Department of Archaeology, University of York, York, UK
| | - Alex Harris
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Alberto Carmagnini
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK
- Palaeogenomics Group, Department of Veterinary Sciences, Ludwig Maximilian University, Munich, Germany
| | - Giedrė Piličiauskienė
- Department of Archeology, Faculty of History, Vilnius University, Vilnius, Lithuania
| | - Tatiana R. Feuerborn
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Lachie Scarsbrook
- The Palaeogenomics and Bio-archaeology Research Network, Research Laboratory for Archaeology and History of Art, University of Oxford, Oxford, UK
| | - Kristina Tabadda
- The Palaeogenomics and Bio-archaeology Research Network, Research Laboratory for Archaeology and History of Art, University of Oxford, Oxford, UK
| | - Povilas Blaževičius
- Department of Archeology, Faculty of History, Vilnius University, Vilnius, Lithuania
- National Museum of Lithuania, Vilnius, Lithuania
| | - Heidi G. Parker
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Shyam Gopalakrishnan
- Center for Evolutionary Hologenomics, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Greger Larson
- The Palaeogenomics and Bio-archaeology Research Network, Research Laboratory for Archaeology and History of Art, University of Oxford, Oxford, UK
| | - Elaine A. Ostrander
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Evan K. Irving-Pease
- Section for Molecular Ecology and Evolution, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| | - Laurent A.F. Frantz
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK
- Palaeogenomics Group, Department of Veterinary Sciences, Ludwig Maximilian University, Munich, Germany
| | - Fernando Racimo
- Section for Molecular Ecology and Evolution, Globe Institute, University of Copenhagen, Copenhagen, Denmark
| |
Collapse
|
148
|
Vitale D, Koretsky M, Kuznetsov N, Hong S, Martin J, James M, Makarious MB, Leonard H, Iwaki H, Faghri F, Blauwendraat C, Singleton AB, Song Y, Levine K, Sreelatha AAK, Fang ZH, Nalls M. GenoTools: An Open-Source Python Package for Efficient Genotype Data Quality Control and Analysis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.26.586362. [PMID: 38585876 PMCID: PMC10996710 DOI: 10.1101/2024.03.26.586362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
GenoTools, a Python package, streamlines population genetics research by integrating ancestry estimation, quality control (QC), and genome-wide association studies (GWAS) capabilities into efficient pipelines. By tracking samples, variants, and quality-specific measures throughout fully customizable pipelines, users can easily manage genetics data for large and small studies. GenoTools' "Ancestry" module renders highly accurate predictions, allowing for high-quality ancestry-specific studies, and enables custom ancestry model training and serialization, specified to the user's genotyping or sequencing platform. As the genotype processing engine that powers several large initiatives, including the NIH's Center for Alzheimer's and Related Dementias (CARD) and the Global Parkinson's Genetics Program (GP2). GenoTools was used to process and analyze the UK Biobank and major Alzheimer's Disease (AD) and Parkinson's Disease (PD) datasets with over 400,000 genotypes from arrays and 5000 sequences and has led to novel discoveries in diverse populations. It has provided replicable ancestry predictions, implemented rigorous QC, and conducted genetic ancestry-specific GWAS to identify systematic errors or biases through a single command. GenoTools is a customizable tool that enables users to efficiently analyze and scale genotype data with reproducible and scalable ancestry, QC, and GWAS pipelines.
Collapse
|
149
|
Lei C, Liu J, Zhang R, Pan Y, Lu Y, Gao Y, Ma X, Yang Y, Guan Y, Mamatyusupu D, Xu S. Ancestral Origins and Admixture History of Kazakhs. Mol Biol Evol 2024; 41:msae144. [PMID: 38995236 PMCID: PMC11272102 DOI: 10.1093/molbev/msae144] [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: 12/15/2023] [Revised: 04/29/2024] [Accepted: 07/02/2024] [Indexed: 07/13/2024] Open
Abstract
Kazakh people, like many other populations that settled in Central Asia, demonstrate an array of mixed anthropological features of East Eurasian (EEA) and West Eurasian (WEA) populations, indicating a possible scenario of biological admixture between already differentiated EEA and WEA populations. However, their complex biological origin, genomic makeup, and genetic interaction with surrounding populations are not well understood. To decipher their genetic structure and population history, we conducted, to our knowledge, the first whole-genome sequencing study of Kazakhs residing in Xinjiang (KZK). We demonstrated that KZK derived their ancestries from 4 ancestral source populations: East Asian (∼39.7%), West Asian (∼28.6%), Siberian (∼23.6%), and South Asian (∼8.1%). The recognizable interactions of EEA and WEA ancestries in Kazakhs were dated back to the 15th century BCE. Kazakhs were genetically distinctive from the Uyghurs in terms of their overall genomic makeup, although the 2 populations were closely related in genetics, and both showed a substantial admixture of western and eastern peoples. Notably, we identified a considerable sex-biased admixture, with an excess of western males and eastern females contributing to the KZK gene pool. We further identified a set of genes that showed remarkable differentiation in KZK from the surrounding populations, including those associated with skin color (SLC24A5, OCA2), essential hypertension (HLA-DQB1), hypertension (MTHFR, SLC35F3), and neuron development (CNTNAP2). These results advance our understanding of the complex history of contacts between Western and Eastern Eurasians, especially those living or along the old Silk Road.
Collapse
Affiliation(s)
- Chang Lei
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Jiaojiao Liu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Rui Zhang
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yuwen Pan
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yan Lu
- Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai 201203, China
| | - Yang Gao
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Xixian Ma
- Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yajun Yang
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Yaqun Guan
- Department of Biochemistry and Molecular Biology, Preclinical Medicine College, Xinjiang Medical University, Urumqi 830011, China
| | - Dolikun Mamatyusupu
- College of the Life Sciences and Technology, Xinjiang University, Urumqi 830046, China
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Center for Evolutionary Biology, School of Life Sciences, Department of Liver Surgery and Transplantation, Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai 200032, China
- Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai 201203, China
| |
Collapse
|
150
|
Chia R, Ray A, Shah Z, Ding J, Ruffo P, Fujita M, Menon V, Saez-Atienzar S, Reho P, Kaivola K, Walton RL, Reynolds RH, Karra R, Sait S, Akcimen F, Diez-Fairen M, Alvarez I, Fanciulli A, Stefanova N, Seppi K, Duerr S, Leys F, Krismer F, Sidoroff V, Zimprich A, Pirker W, Rascol O, Foubert-Samier A, Meissner WG, Tison F, Pavy-Le Traon A, Pellecchia MT, Barone P, Russillo MC, Marín-Lahoz J, Kulisevsky J, Torres S, Mir P, Periñán MT, Proukakis C, Chelban V, Wu L, Goh YY, Parkkinen L, Hu MT, Kobylecki C, Saxon JA, Rollinson S, Garland E, Biaggioni I, Litvan I, Rubio I, Alcalay RN, Kwei KT, Lubbe SJ, Mao Q, Flanagan ME, Castellani RJ, Khurana V, Ndayisaba A, Calvo A, Mora G, Canosa A, Floris G, Bohannan RC, Moore A, Norcliffe-Kaufmann L, Palma JA, Kaufmann H, Kim C, Iba M, Masliah E, Dawson TM, Rosenthal LS, Pantelyat A, Albert MS, Pletnikova O, Troncoso JC, Infante J, Lage C, Sánchez-Juan P, Serrano GE, Beach TG, Pastor P, Morris HR, Albani D, Clarimon J, Wenning GK, Hardy JA, Ryten M, Topol E, Torkamani A, Chiò A, Bennett DA, De Jager PL, Low PA, Singer W, Cheshire WP, Wszolek ZK, Dickson DW, Traynor BJ, Gibbs JR, Dalgard CL, Ross OA, Houlden H, Scholz SW. Genome sequence analyses identify novel risk loci for multiple system atrophy. Neuron 2024; 112:2142-2156.e5. [PMID: 38701790 PMCID: PMC11223971 DOI: 10.1016/j.neuron.2024.04.002] [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: 09/04/2023] [Revised: 02/28/2024] [Accepted: 04/02/2024] [Indexed: 05/05/2024]
Abstract
Multiple system atrophy (MSA) is an adult-onset, sporadic synucleinopathy characterized by parkinsonism, cerebellar ataxia, and dysautonomia. The genetic architecture of MSA is poorly understood, and treatments are limited to supportive measures. Here, we performed a comprehensive analysis of whole genome sequence data from 888 European-ancestry MSA cases and 7,128 controls to systematically investigate the genetic underpinnings of this understudied neurodegenerative disease. We identified four significantly associated risk loci using a genome-wide association study approach. Transcriptome-wide association analyses prioritized USP38-DT, KCTD7, and lnc-KCTD7-2 as novel susceptibility genes for MSA within these loci, and single-nucleus RNA sequence analysis found that the associated variants acted as cis-expression quantitative trait loci for multiple genes across neuronal and glial cell types. In conclusion, this study highlights the role of genetic determinants in the pathogenesis of MSA, and the publicly available data from this study represent a valuable resource for investigating synucleinopathies.
Collapse
Affiliation(s)
- Ruth Chia
- Neuromuscular Diseases Research Section, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Anindita Ray
- Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Zalak Shah
- Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Jinhui Ding
- Computational Biology Group, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Paola Ruffo
- Neuromuscular Diseases Research Section, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA; Medical Genetics Laboratory, Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, Rende, Italy
| | - Masashi Fujita
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center and the Taub Institute for Research on Alzheimer's Disease and the Aging Brain, New York, NY, USA
| | - Vilas Menon
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center and the Taub Institute for Research on Alzheimer's Disease and the Aging Brain, New York, NY, USA
| | - Sara Saez-Atienzar
- Neuromuscular Diseases Research Section, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Paolo Reho
- Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Karri Kaivola
- Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Ronald L Walton
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Regina H Reynolds
- NIHR Great Ormond Street Hospital Biomedical Research Centre, University College London, London, UK; Great Ormond Street Institute of Child Health, Genetics and Genomic Medicine, University College London, London, UK; Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Ramita Karra
- Neuromuscular Diseases Research Section, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Shaimaa Sait
- Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Fulya Akcimen
- Neuromuscular Diseases Research Section, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Monica Diez-Fairen
- Memory and Movement Disorders Units, Department of Neurology, University Hospital Mutua de Terrassa, Barcelona, Spain
| | - Ignacio Alvarez
- Memory and Movement Disorders Units, Department of Neurology, University Hospital Mutua de Terrassa, Barcelona, Spain
| | | | - Nadia Stefanova
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Klaus Seppi
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Susanne Duerr
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Fabian Leys
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Florian Krismer
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Victoria Sidoroff
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | | | - Walter Pirker
- Department of Neurology, Klinik Ottakring - Wilhelminenspital, Vienna, Austria
| | - Olivier Rascol
- MSA French Reference Center and CIC-1436, Department of Clinical Pharmacology and Neurosciences, University of Toulouse, Toulouse, France
| | - Alexandra Foubert-Samier
- Service de Neurologie des Maladies Neurodégénératives, French Reference Center for MSA, NS-Park/FCRIN Network, CHU Bordeaux, Bordeaux, France
| | - Wassilios G Meissner
- Service de Neurologie des Maladies Neurodégénératives, French Reference Center for MSA, NS-Park/FCRIN Network, CHU Bordeaux, Bordeaux, France; University of Bordeaux, CNRS, IMN, UMR 5293, Bordeaux, France; Department of Medicine, University of Otago, and the New Zealand Brain Research Institute, Christchurch, New Zealand
| | - François Tison
- Service de Neurologie des Maladies Neurodégénératives, French Reference Center for MSA, NS-Park/FCRIN Network, CHU Bordeaux, Bordeaux, France; University of Bordeaux, CNRS, IMN, UMR 5293, Bordeaux, France
| | - Anne Pavy-Le Traon
- French Reference Center for MSA, Department of Neurosciences, Centre d'Investigation Clinique de Toulouse CIC1436, UMR 1048, Institute of Cardiovascular and Metabolic Diseases (I2MC), University Hospital of Toulouse, INSERM, Toulouse, France
| | - Maria Teresa Pellecchia
- Neuroscience Section, Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, Salerno, Italy
| | - Paolo Barone
- Neuroscience Section, Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, Salerno, Italy
| | - Maria Claudia Russillo
- Neuroscience Section, Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, Salerno, Italy
| | - Juan Marín-Lahoz
- Movement Disorders Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain; Institut d'Investigacions Biomèdiques Sant Pau (IIB-Sant Pau), Centro de Investigación en Red Enfermedades Neurodegenerativas (CIBERNED), Universitat Autònoma de Barcelona, Barcelona, Spain; Servicio de Neurología, Hospital Universitario Miguel Servet, Zaragoza, Spain
| | - Jaime Kulisevsky
- Movement Disorders Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain; Institut d'Investigacions Biomèdiques Sant Pau (IIB-Sant Pau), Centro de Investigación en Red Enfermedades Neurodegenerativas (CIBERNED), Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Soraya Torres
- Institut d'Investigacions Biomèdiques Sant Pau (IIB-Sant Pau), Centro de Investigación en Red Enfermedades Neurodegenerativas (CIBERNED), Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Pablo Mir
- Unidad de Trastornos del Movimiento Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla Hospital Universitario Virgen del Rocío, Universidad de Sevilla, Seville, Spain; Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Madrid, Spain; Departamento de Medicina Facultad de Medicina, Universidad de Sevilla, Seville, Spain
| | - Maria Teresa Periñán
- Unidad de Trastornos del Movimiento Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla Hospital Universitario Virgen del Rocío, Universidad de Sevilla, Seville, Spain; Centre for Preventive Neurology, Wolfson Institute of Population Health, Queen Mary University, London, UK
| | - Christos Proukakis
- Department of Clinical and Movement Neurosciences, University College London Queen Square Institute of Neurology, London, UK
| | - Viorica Chelban
- Department of Neuromuscular Diseases, University College London Queen Square Institute of Neurology, London, UK; The National Hospital for Neurology and Neurosurgery, London, UK
| | - Lesley Wu
- Department of Neuromuscular Diseases, University College London Queen Square Institute of Neurology, London, UK
| | - Yee Y Goh
- Department of Neuromuscular Diseases, University College London Queen Square Institute of Neurology, London, UK
| | - Laura Parkkinen
- Nuffield Department of Clinical Neurosciences, Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
| | - Michele T Hu
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Christopher Kobylecki
- Department of Neurology, Northern Care Alliance NHS Foundation Trust, Manchester Academic Health Sciences Centre, The University of Manchester, Manchester, UK
| | - Jennifer A Saxon
- Cerebral Function Unit, Manchester Centre for Clinical Neurosciences, Salfort, UK; Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Sara Rollinson
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Emily Garland
- Autonomic Dysfunction Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Italo Biaggioni
- Autonomic Dysfunction Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Irene Litvan
- Department of Neurosciences, University of California, San Diego, San Diego, CA, USA
| | - Ileana Rubio
- Department of Neurosciences, University of California, San Diego, San Diego, CA, USA
| | - Roy N Alcalay
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA; Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
| | - Kimberly T Kwei
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
| | - Steven J Lubbe
- Ken and Ruth Davee Department of Neurology and Simpson Querrey Center for Neurogenetics, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Qinwen Mao
- Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Northwestern University Feinberg School of Medicine, Chicago, IL, USA; Department of Pathology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Margaret E Flanagan
- Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Northwestern University Feinberg School of Medicine, Chicago, IL, USA; Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, TX, USA; Department of Pathology, UT Health San Antonio, San Antonio, TX, USA
| | - Rudolph J Castellani
- Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Vikram Khurana
- Ann Romney Center for Neurologic Disease, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Harvard Stem Cell Institute, Cambridge, MA, USA
| | - Alain Ndayisaba
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria; Ann Romney Center for Neurologic Disease, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Andrea Calvo
- "Rita Levi Montalcini" Department of Neuroscience, University of Turin, Turin, Italy
| | - Gabriele Mora
- Istituti Clinici Scientifici Maugeri, IRCCS, Milan, Italy
| | - Antonio Canosa
- "Rita Levi Montalcini" Department of Neuroscience, University of Turin, Turin, Italy
| | - Gianluca Floris
- Department of Neurology, University Hospital of Cagliari, Cagliari, Italy
| | - Ryan C Bohannan
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, USA
| | - Anni Moore
- Computational Biology Group, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | | | - Jose-Alberto Palma
- Department of Neurology, New York University School of Medicine, New York, NY, USA
| | - Horacio Kaufmann
- Department of Neurology, New York University School of Medicine, New York, NY, USA
| | - Changyoun Kim
- Molecular Neuropathology Section, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Michiyo Iba
- Molecular Neuropathology Section, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Eliezer Masliah
- Molecular Neuropathology Section, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Ted M Dawson
- Department of Neurology, Johns Hopkins University Medical Center, Baltimore, MD, USA; Neuroregeneration and Stem Cell Programs, Institute of Cell Engineering, Johns Hopkins University Medical Center, Baltimore, MD, USA; Department of Pharmacology and Molecular Science, Johns Hopkins University Medical Center, Baltimore, MD, USA; Solomon H. Snyder Department of Neuroscience, Johns Hopkins University Medical Center, Baltimore, MD, USA
| | - Liana S Rosenthal
- Department of Neurology, Johns Hopkins University Medical Center, Baltimore, MD, USA
| | - Alexander Pantelyat
- Department of Neurology, Johns Hopkins University Medical Center, Baltimore, MD, USA
| | - Marilyn S Albert
- Department of Neurology, Johns Hopkins University Medical Center, Baltimore, MD, USA
| | - Olga Pletnikova
- Department of Pathology (Neuropathology), Johns Hopkins University Medical Center, Baltimore, MD, USA; Department of Pathology and Anatomical Sciences, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA
| | - Juan C Troncoso
- Department of Pathology (Neuropathology), Johns Hopkins University Medical Center, Baltimore, MD, USA
| | - Jon Infante
- Neurology Service, University Hospital Marqués de Valdecilla-IDIVAL-UC-CIBERNED, Santander, Spain
| | - Carmen Lage
- Neurology Service, University Hospital Marqués de Valdecilla-IDIVAL-UC-CIBERNED, Santander, Spain
| | - Pascual Sánchez-Juan
- Neurology Service, University Hospital Marqués de Valdecilla-IDIVAL-UC-CIBERNED, Santander, Spain; Alzheimer's Centre Reina Sofia-CIEN Foundation-ISCIII, Madrid, Spain
| | - Geidy E Serrano
- Civin Laboratory for Neuropathology, Banner Sun Health Research Institute, Sun City, AZ, USA
| | - Thomas G Beach
- Civin Laboratory for Neuropathology, Banner Sun Health Research Institute, Sun City, AZ, USA
| | - Pau Pastor
- Genomics and Transcriptomics of Synucleinopathies, Neurosciences, The Germans Trias i Pujol Research Institute (IGTP), Badalona, Barcelona, Spain; Unit of Neurodegenerative Diseases, Department of Neurology, University Hospital Germans Trias i Pujol, Badalona, Barcelona, Spain
| | - Huw R Morris
- Department of Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Diego Albani
- Department of Neuroscience, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Jordi Clarimon
- Sant Pau Biomedical Research Institute, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain; The Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Gregor K Wenning
- Autonomic Unit - Division of Neurobiology, Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - John A Hardy
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK; UK Dementia Research Institute of UCL, UCL Institute of Neurology, University College London, London, UK; Reta Lila Weston Institute, UCL Queen Square Institute of Neurology, University College London, London, UK; UCL Movement Disorders Centre, University College London, London, UK; Institute for Advanced Study, The Hong Kong University of Science and Technology, Hong Kong SAR, China
| | - Mina Ryten
- NIHR Great Ormond Street Hospital Biomedical Research Centre, University College London, London, UK; Great Ormond Street Institute of Child Health, Genetics and Genomic Medicine, University College London, London, UK
| | - Eric Topol
- Scripps Research Translational Institute, Scripps Research, La Jolla, CA, USA
| | - Ali Torkamani
- Scripps Research Translational Institute, Scripps Research, La Jolla, CA, USA
| | - Adriano Chiò
- "Rita Levi Montalcini" Department of Neuroscience, University of Turin, Turin, Italy; Institute of Cognitive Sciences and Technologies, C.N.R., Rome, Italy; Azienda Ospedaliero Universitaria Città della Salute e della Scienza, Turin, Italy
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Philip L De Jager
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center and the Taub Institute for Research on Alzheimer's Disease and the Aging Brain, New York, NY, USA
| | - Philip A Low
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | | | | | | | | | - Bryan J Traynor
- Neuromuscular Diseases Research Section, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA; Department of Neurology, Johns Hopkins University Medical Center, Baltimore, MD, USA; RNA Therapeutics Laboratory, Therapeutics Development Branch, National Center for Advancing Translational Sciences, Rockville, MD, USA
| | - J Raphael Gibbs
- Computational Biology Group, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Clifton L Dalgard
- Department of Anatomy, Physiology and Genetics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Owen A Ross
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA; Department of Clinical Genomics, Mayo Clinic, Jacksonville, FL, USA
| | - Henry Houlden
- Department of Neuromuscular Diseases, University College London Queen Square Institute of Neurology, London, UK; The National Hospital for Neurology and Neurosurgery, London, UK
| | - Sonja W Scholz
- Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA; Department of Neurology, Johns Hopkins University Medical Center, Baltimore, MD, USA.
| |
Collapse
|