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Lim A, Pasini M, Yun S, Gill J, Koirala B. Genetic association between post-traumatic stress disorder and cardiovascular disease: A scoping review. J Psychiatr Res 2024; 178:331-348. [PMID: 39191203 DOI: 10.1016/j.jpsychires.2024.08.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Revised: 07/05/2024] [Accepted: 08/14/2024] [Indexed: 08/29/2024]
Abstract
INTRODUCTION Post-traumatic stress disorder (PTSD) is a complex psychiatric disorder associated with adverse long-term health outcomes, including cardiovascular disease (CVD). Despite growing evidence that PTSD is positively associated with CVD, the biological mechanisms underlying this association are poorly understood. This review provides an overview of the current state of science on the genetic association between PTSD and CVD. MATERIAL AND METHODS This scoping review identified studies from Pubmed, Embase, PsycINFO, and Web of Science. The search terms were a combination of PTSD, CVD/CVD-related traits, and a set of genetic molecules and related terms. This review followed the PRISMA Extension for Scoping Reviews guidelines. Eligible criteria included original studies that have genetic factors related to PTSD or CVD, conducted in humans, written in English, and published between 2003 and 2023 in peer-reviewed journals. RESULTS A total of twenty-three studies were included; PTSD correlated with genetic variants in CVD-related traits and gene expression in regulatory pathways contributing to CVD development. Common CVD-related traits involved in genetic associations with PTSD were inflammation, cellular aging, increased blood pressure, hypothalamus-pituitary-adrenal axis dysregulation, metabolic syndrome, and oxidative stress. These traits may explain potential underlying mechanisms between PTSD and CVD. Evidence of a causal relationship between the two diseases was insufficient. DISCUSSION PTSD and CVD/CVD-related traits are genetically associated. Further research is needed to comprehensively explore gene-environment interactions and the cumulative impact of behavioral and psychological factors on the pathophysiological mechanisms between PTSD and CVD.
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Affiliation(s)
- Arum Lim
- Johns Hopkins School of Nursing, 525 N. Wolfe St., Baltimore, MD, USA.
| | - Mia Pasini
- Johns Hopkins School of Nursing, 525 N. Wolfe St., Baltimore, MD, USA
| | - Sijung Yun
- Johns Hopkins School of Nursing, 525 N. Wolfe St., Baltimore, MD, USA
| | - Jessica Gill
- Johns Hopkins School of Nursing, 525 N. Wolfe St., Baltimore, MD, USA
| | - Binu Koirala
- Johns Hopkins School of Nursing, 525 N. Wolfe St., Baltimore, MD, USA
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2
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Köroğlu Ç, Chen P, Traurig M, Altok S, Bogardus C, Baier LJ. De Novo Genome Assemblies From Two Indigenous Americans from Arizona Identify New Polymorphisms in Non-Reference Sequences. Genome Biol Evol 2024; 16:evae188. [PMID: 39190003 PMCID: PMC11384899 DOI: 10.1093/gbe/evae188] [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: 11/08/2023] [Revised: 05/17/2024] [Accepted: 08/22/2024] [Indexed: 08/28/2024] Open
Abstract
There is a collective push to diversify human genetic studies by including underrepresented populations. However, analyzing DNA sequence reads involves the initial step of aligning the reads to the GRCh38/hg38 reference genome which is inadequate for non-European ancestries. In this study, using long-read sequencing technology, we constructed de novo genome assemblies from two indigenous Americans from Arizona (IAZ). Each assembly included ∼17 Mb of DNA sequence not present [nonreference sequence (NRS)] in hg38, which consists mostly of repeat elements. Forty NRSs totaling 240 kb were uniquely anchored to the hg38 primary assembly generating a modified hg38-NRS reference genome. DNA sequence alignment and variant calling were then conducted with whole-genome sequencing (WGS) sequencing data from 387 IAZ using both the hg38 and modified hg38-NRS reference maps. Variant calling with the hg38-NRS map identified ∼50,000 single-nucleotide variants present in at least 5% of the WGS samples which were not detected with the hg38 reference map. We also directly assessed the NRSs positioned within genes. Seventeen NRSs anchored to regions including an identical 187 bp NRS found in both de novo assemblies. The NRS is located in HCN2 79 bp downstream of Exon 3 and contains several putative transcriptional regulatory elements. Genotyping of the HCN2-NRS revealed that the insertion is enriched in IAZ (minor allele frequency = 0.45) compared to other reference populations tested. This study shows that inclusion of population-specific NRSs can dramatically change the variant profile in an underrepresented ethnic groups and thereby lead to the discovery of previously missed common variations.
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Affiliation(s)
- Çiğdem Köroğlu
- Diabetes Molecular Genetics Section, Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ 85004, USA
| | - Peng Chen
- Diabetes Molecular Genetics Section, Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ 85004, USA
| | - Michael Traurig
- Diabetes Molecular Genetics Section, Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ 85004, USA
| | - Serdar Altok
- Diabetes Molecular Genetics Section, Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ 85004, USA
| | - Clifton Bogardus
- Diabetes Molecular Genetics Section, Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ 85004, USA
| | - Leslie J Baier
- Diabetes Molecular Genetics Section, Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ 85004, USA
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Moreno-Grau S, Vernekar M, Lopez-Pineda A, Mas-Montserrat D, Barrabés M, Quinto-Cortés CD, Moatamed B, Lee MTM, Yu Z, Numakura K, Matsuda Y, Wall JD, Ioannidis AG, Katsanis N, Takano T, Bustamante CD. Polygenic risk score portability for common diseases across genetically diverse populations. Hum Genomics 2024; 18:93. [PMID: 39218908 PMCID: PMC11367857 DOI: 10.1186/s40246-024-00664-y] [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: 06/15/2024] [Accepted: 08/19/2024] [Indexed: 09/04/2024] Open
Abstract
BACKGROUND Polygenic risk scores (PRS) derived from European individuals have reduced portability across global populations, limiting their clinical implementation at worldwide scale. Here, we investigate the performance of a wide range of PRS models across four ancestry groups (Africans, Europeans, East Asians, and South Asians) for 14 conditions of high-medical interest. METHODS To select the best-performing model per trait, we first compared PRS performances for publicly available scores, and constructed new models using different methods (LDpred2, PRS-CSx and SNPnet). We used 285 K European individuals from the UK Biobank (UKBB) for training and 18 K, including diverse ancestries, for testing. We then evaluated PRS portability for the best models in Europeans and compared their accuracies with respect to the best PRS per ancestry. Finally, we validated the selected PRS models using an independent set of 8,417 individuals from Biobank of the Americas-Genomelink (BbofA-GL); and performed a PRS-Phewas. RESULTS We confirmed a decay in PRS performances relative to Europeans when the evaluation was conducted using the best-PRS model for Europeans (51.3% for South Asians, 46.6% for East Asians and 39.4% for Africans). We observed an improvement in the PRS performances when specifically selecting ancestry specific PRS models (phenotype variance increase: 1.62 for Africans, 1.40 for South Asians and 0.96 for East Asians). Additionally, when we selected the optimal model conditional on ancestry for CAD, HDL-C and LDL-C, hypertension, hypothyroidism and T2D, PRS performance for studied populations was more comparable to what was observed in Europeans. Finally, we were able to independently validate tested models for Europeans, and conducted a PRS-Phewas, identifying cross-trait interplay between cardiometabolic conditions, and between immune-mediated components. CONCLUSION Our work comprehensively evaluated PRS accuracy across a wide range of phenotypes, reducing the uncertainty with respect to which PRS model to choose and in which ancestry group. This evaluation has let us identify specific conditions where implementing risk-prioritization strategies could have practical utility across diverse ancestral groups, contributing to democratizing the implementation of PRS.
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Affiliation(s)
- Sonia Moreno-Grau
- Galatea Bio, Inc, 14350 Commerce Way, Miami Lakes, FL, 33146, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, 1265 Welch Road, Stanford, CA, 94305, USA
| | - Manvi Vernekar
- Genomelink, Inc, 2150 Shattuck Avenue, Berkeley, CA, 94704, USA
| | - Arturo Lopez-Pineda
- Galatea Bio, Inc, 14350 Commerce Way, Miami Lakes, FL, 33146, USA
- , Amphora Health. Batallon Independencia 80, Morelia, Michoacan, 58260, Mexico
- Escuela Nacional de Estudios Superiores, Unidad Morelia, Universidad Nacional Autonoma de México, Antigua Carretera a Pátzcuaro No. 8701, Col. Ex Hacienda de San José de la Huerta, Morelia, Michoacán, C.P. 58190, Mexico
| | | | - Míriam Barrabés
- Galatea Bio, Inc, 14350 Commerce Way, Miami Lakes, FL, 33146, USA
| | | | - Babak Moatamed
- Galatea Bio, Inc, 14350 Commerce Way, Miami Lakes, FL, 33146, USA
| | | | - Zhenning Yu
- Genomelink, Inc, 2150 Shattuck Avenue, Berkeley, CA, 94704, USA
| | | | - Yuta Matsuda
- Genomelink, Inc, 2150 Shattuck Avenue, Berkeley, CA, 94704, USA
| | - Jeffrey D Wall
- Galatea Bio, Inc, 14350 Commerce Way, Miami Lakes, FL, 33146, USA
| | - Alexander G Ioannidis
- Galatea Bio, Inc, 14350 Commerce Way, Miami Lakes, FL, 33146, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, 1265 Welch Road, Stanford, CA, 94305, USA
- University of California Santa Cruz, 1156 High Street, Santa Cruz, CA, 95064, USA
| | | | - Tomohiro Takano
- Genomelink, Inc, 2150 Shattuck Avenue, Berkeley, CA, 94704, USA.
- Japan: Awakens Japan K.K. (Japanese subsidiary of Genomelink, Inc.), 2-11-3, Meguro, Meguro-ku, 1530063, Tokyo, Japan.
| | - Carlos D Bustamante
- Galatea Bio, Inc, 14350 Commerce Way, Miami Lakes, FL, 33146, USA.
- Department of Biomedical Data Science, Stanford University School of Medicine, 1265 Welch Road, Stanford, CA, 94305, USA.
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Kullo IJ. Promoting equity in polygenic risk assessment through global collaboration. Nat Genet 2024; 56:1780-1787. [PMID: 39103647 DOI: 10.1038/s41588-024-01843-2] [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: 05/11/2023] [Accepted: 06/24/2024] [Indexed: 08/07/2024]
Abstract
The long delay before genomic technologies become available in low- and middle-income countries is a concern from both scientific and ethical standpoints. Polygenic risk scores (PRSs), a relatively recent advance in genomics, could have a substantial impact on promoting health by improving disease risk prediction and guiding preventive strategies. However, clinical use of PRSs in their current forms might widen global health disparities, as their portability to diverse groups is limited. This Perspective highlights the need for global collaboration to develop and implement PRSs that perform equitably across the world. Such collaboration requires capacity building and the generation of new data in low-resource settings, the sharing of harmonized genotype and phenotype data securely across borders, novel population genetics and statistical methods to improve PRS performance, and thoughtful clinical implementation in diverse settings. All this needs to occur while considering the ethical, legal and social implications, with support from regulatory and funding agencies and policymakers.
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Affiliation(s)
- Iftikhar J Kullo
- Department of Cardiovascular Medicine and the Gonda Vascular Center, Mayo Clinic, Rochester, MN, USA.
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Takayama J, Makino S, Funayama T, Ueki M, Narita A, Murakami K, Orui M, Ishikuro M, Obara T, Kuriyama S, Yamamoto M, Tamiya G. A fine-scale genetic map of the Japanese population. Clin Genet 2024; 106:284-292. [PMID: 38719617 DOI: 10.1111/cge.14536] [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: 10/03/2023] [Revised: 04/13/2024] [Accepted: 04/15/2024] [Indexed: 08/13/2024]
Abstract
Genetic maps are fundamental resources for linkage and association studies. A fine-scale genetic map can be constructed by inferring historical recombination events from the genome-wide structure of linkage disequilibrium-a non-random association of alleles among loci-by using population-scale sequencing data. We constructed a fine-scale genetic map and identified recombination hotspots from 10 092 551 bi-allelic high-quality autosomal markers segregating among 150 unrelated Japanese individuals whose genotypes were determined by high-coverage (30×) whole-genome sequencing, and the genotype quality was carefully controlled by using their parents' and offspring's genotypes. The pedigree information was also utilized for haplotype phasing. The resulting genome-wide recombination rate profiles were concordant with those of the worldwide population on a broad scale, and the resolution was much improved. We identified 9487 recombination hotspots and confirmed the enrichment of previously known motifs in the hotspots. Moreover, we demonstrated that the Japanese genetic map improved the haplotype phasing and genotype imputation accuracy for the Japanese population. The construction of a population-specific genetic map will help make genetics research more accurate.
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Affiliation(s)
- Jun Takayama
- Department of AI and Innovative Medicine, Tohoku University School of Medicine, Sendai, Japan
- Department of Integrative Genomics, Tohoku Medical Megabank Organization (ToMMo) Tohoku University, Sendai, Japan
- Statistical Genetics Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
| | - Satoshi Makino
- Department of Integrative Genomics, Tohoku Medical Megabank Organization (ToMMo) Tohoku University, Sendai, Japan
| | - Takamitsu Funayama
- Department of Integrative Genomics, Tohoku Medical Megabank Organization (ToMMo) Tohoku University, Sendai, Japan
- Statistical Genetics Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
| | - Masao Ueki
- Statistical Genetics Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
| | - Akira Narita
- Department of Integrative Genomics, Tohoku Medical Megabank Organization (ToMMo) Tohoku University, Sendai, Japan
| | - Keiko Murakami
- Department of Preventive Medicine and Epidemiology, ToMMo, Tohoku University, Sendai, Japan
| | - Masatsugu Orui
- Department of Preventive Medicine and Epidemiology, ToMMo, Tohoku University, Sendai, Japan
- Department of Molecular Epidemiology, Tohoku University School of Medicine, Sendai, Japan
| | - Mami Ishikuro
- Department of Preventive Medicine and Epidemiology, ToMMo, Tohoku University, Sendai, Japan
- Department of Molecular Epidemiology, Tohoku University School of Medicine, Sendai, Japan
| | - Taku Obara
- Department of Preventive Medicine and Epidemiology, ToMMo, Tohoku University, Sendai, Japan
- Department of Molecular Epidemiology, Tohoku University School of Medicine, Sendai, Japan
| | - Shinichi Kuriyama
- Department of Preventive Medicine and Epidemiology, ToMMo, Tohoku University, Sendai, Japan
- Department of Molecular Epidemiology, Tohoku University School of Medicine, Sendai, Japan
| | - Masayuki Yamamoto
- Department of Integrative Genomics, Tohoku Medical Megabank Organization (ToMMo) Tohoku University, Sendai, Japan
| | - Gen Tamiya
- Department of AI and Innovative Medicine, Tohoku University School of Medicine, Sendai, Japan
- Department of Integrative Genomics, Tohoku Medical Megabank Organization (ToMMo) Tohoku University, Sendai, Japan
- Statistical Genetics Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
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6
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Bibi A, Ji W, Jeffries L, Zerillo C, Konstantino M, Mis EK, Khursheed F, Khokha MK, Lakhani SA, Malik S. Exome sequencing reveals genetic heterogeneity in consanguineous Pakistani families with neurodevelopmental and neuromuscular disorders. AMERICAN JOURNAL OF MEDICAL GENETICS. PART C, SEMINARS IN MEDICAL GENETICS 2024:e32103. [PMID: 39152716 DOI: 10.1002/ajmg.c.32103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2024] [Revised: 07/15/2024] [Accepted: 07/26/2024] [Indexed: 08/19/2024]
Abstract
There remains a crucial need to address inequalities in genomic research and include populations from low- and middle-income countries (LMIC). Here we present eight consanguineous families from Pakistan, five with neurodevelopmental disorders (NDDs) and three with neuromuscular disorders (NMDs). Affected individuals were clinically characterized, and genetic variants were identified through exome sequencing (ES), followed by family segregation analysis. Affected individuals in six out of eight families (75%) carried homozygous variants that met ACMG criteria for being pathogenic (in the genes ADGRG1, METTL23, SPG11) or likely pathogenic (in the genes GPAA1, MFN2, SGSH). The remaining two families had homozygous candidate variants in the genes (AP4M1 and FAM126A) associated with phenotypes consistent with their clinical presentations, but the variants did not meet the criteria for pathogenicity and were hence classified as variants of unknown significance. Notably, the variants in ADGRG1, AP4M1, FAM126A, and SGSH did not have prior reports in the literature, demonstrating the importance of including diverse populations in genomic studies. We provide clinical phenotyping along with analyses of ES data that support the utility of ES in making accurate molecular diagnoses in these patients, as well as in unearthing novel variants in known disease-causing genes in underrepresented populations from LMIC.
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Affiliation(s)
- Anisa Bibi
- Human Genetics Program, Department of Zoology, Quaid-i-Azam University, Islamabad, Pakistan
- Pediatric Genomics Discovery Program, Department of Pediatrics, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Weizhen Ji
- Pediatric Genomics Discovery Program, Department of Pediatrics, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Lauren Jeffries
- Pediatric Genomics Discovery Program, Department of Pediatrics, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Cynthia Zerillo
- Pediatric Genomics Discovery Program, Department of Pediatrics, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Monica Konstantino
- Pediatric Genomics Discovery Program, Department of Pediatrics, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Emily K Mis
- Pediatric Genomics Discovery Program, Department of Pediatrics, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Filza Khursheed
- Human Genetics Program, Department of Zoology, Quaid-i-Azam University, Islamabad, Pakistan
| | - Mustafa K Khokha
- Pediatric Genomics Discovery Program, Department of Pediatrics, Yale University School of Medicine, New Haven, Connecticut, USA
- Department of Genetics, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Saquib A Lakhani
- Pediatric Genomics Discovery Program, Department of Pediatrics, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Sajid Malik
- Human Genetics Program, Department of Zoology, Quaid-i-Azam University, Islamabad, Pakistan
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Deepthi B, Krishnasamy S, Krishnamurthy S, Khandelwal P, Sinha A, Hari P, Jaikumar R, Agrawal P, Saha A, Deepthi RV, Agarwal I, Sinha R, Venkatachari M, Shah MA, Bhatt GC, Krishnan B, Vasudevan A, Bagga A, Krishnamurthy S. Clinical characteristics and genetic profile of children with WDR72-associated distal renal tubular acidosis: a nationwide experience. Pediatr Nephrol 2024:10.1007/s00467-024-06478-3. [PMID: 39150521 DOI: 10.1007/s00467-024-06478-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2024] [Revised: 07/22/2024] [Accepted: 07/22/2024] [Indexed: 08/17/2024]
Abstract
BACKGROUND Limited data, primarily from small case series, exist regarding the clinical profile, genetic variants, and outcomes of WDR72-associated distal renal tubular acidosis (WDR72-dRTA). METHODS Our study enrolled children diagnosed with WDR72-dRTA below 18 years of age from 9 Indian centers and analyzed their clinical characteristics, genetic profiles, and outcomes. Potential genotype-phenotype correlations were explored. RESULTS We report 22 patients (59% female) with WDR72-dRTA who were diagnosed at a median age of 5.3 (3, 8) years with polyuria (n = 17; 77.3%), poor growth (16; 72.7%), and rickets (9; 40.9%). Amelogenesis imperfecta was present in 21 (95.5%) cases. At presentation, all patients had normal anion gap metabolic acidosis; hypokalemia and nephrocalcinosis were seen in 17 (77.3%) patients each. Seven (31.8%) patients had concomitant proximal tubular dysfunction. Genetic analysis identified biallelic nonsense variants in 18 (81.8%) patients, including novel variants in 6 cases. A previously reported variant, c.88C > T, and a novel variant, c.655C > T, were the most frequent variants, accounting for 10 (45.5%) cases. Over a median follow-up of 1.3 (1, 8) years, the height velocity improved by 0.74 (0.2, 1.2) standard deviation scores, while 3 children (13.6%) progressed to chronic kidney disease (CKD) stage 2, with eGFR ranging from 67 to 76 mL/min/1.73 m2, respectively, after 11.3-16 years of follow-up. No specific genotype-phenotype correlation could be established. CONCLUSIONS WDR72-dRTA should be considered in children with typical features of amelogenesis imperfecta and dRTA. Biallelic nonsense variants are common in Asians. While most patients respond well to treatment with improved growth and preserved eGFR, on long-term follow-up, a decline in eGFR may occur.
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Affiliation(s)
- Bobbity Deepthi
- Pediatric Nephrology Services, Department of Pediatrics, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Pondicherry, India
| | - Sudarsan Krishnasamy
- Pediatric Nephrology Services, Department of Pediatrics, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Pondicherry, India
| | | | - Priyanka Khandelwal
- Division of Pediatric Nephrology, Department of Pediatrics, All India Institute of Medical Sciences (AIIMS), New Delhi, India
| | - Aditi Sinha
- Division of Pediatric Nephrology, Department of Pediatrics, All India Institute of Medical Sciences (AIIMS), New Delhi, India
| | - Pankaj Hari
- Division of Pediatric Nephrology, Department of Pediatrics, All India Institute of Medical Sciences (AIIMS), New Delhi, India
| | - Rohitha Jaikumar
- Division of Pediatric Nephrology, Department of Pediatrics, Lady Hardinge Medical College, New Delhi, India
| | - Prajal Agrawal
- Division of Pediatric Nephrology, Department of Pediatrics, Lady Hardinge Medical College, New Delhi, India
| | - Abhijeet Saha
- Division of Pediatric Nephrology, Department of Pediatrics, Lady Hardinge Medical College, New Delhi, India
| | - R V Deepthi
- Division of Pediatric Nephrology, Department of Pediatrics, Christian Medical College, Vellore, India
| | - Indira Agarwal
- Division of Pediatric Nephrology, Department of Pediatrics, Christian Medical College, Vellore, India
| | - Rajiv Sinha
- Division of Pediatric Nephrology, Institute of Child Health, Kolkata, India
| | - Mahesh Venkatachari
- Department of Pediatrics, All India Institute of Medical Sciences, Mangalagiri, India
| | - Mehul A Shah
- Little Star Children's Hospital, Hyderabad, India
| | - Girish Chandra Bhatt
- Division of Pediatric Nephrology, Department of Pediatrics, All India Institute of Medical Sciences, Bhopal, India
| | - Balasubramanian Krishnan
- Department of Dentistry, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Pondicherry, India
| | - Anil Vasudevan
- Division of Molecular Medicine, St. John's Research Institute, Bangalore, India
- Department of Pediatric Nephrology, St. John's Medical College Hospital, Bangalore, India
| | - Arvind Bagga
- Division of Pediatric Nephrology, Department of Pediatrics, All India Institute of Medical Sciences (AIIMS), New Delhi, India
| | - Sriram Krishnamurthy
- Pediatric Nephrology Services, Department of Pediatrics, Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), Pondicherry, India.
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8
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Li C, Hou Y, Ou R, Wei Q, Zhang L, Liu K, Lin J, Chen X, Song W, Zhao B, Wu Y, Shang H. GWAS Identifies DPP6 as Risk Gene of Cognitive Decline in Parkinson's Disease. J Gerontol A Biol Sci Med Sci 2024; 79:glae155. [PMID: 38875006 PMCID: PMC11272050 DOI: 10.1093/gerona/glae155] [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: 02/26/2024] [Indexed: 06/15/2024] Open
Abstract
BACKGROUND Cognitive decline is among the most common non-motor symptoms in Parkinson's disease (PD), while its physiological mechanisms remain poorly understood. Genetic factors constituted a fundamental determinant in the heterogeneity of cognitive decline among PD patients. However, the underlying genetic background was still less studied. METHODS To explore the genetic determinants contributing to cognitive decline in PD, we performed genome-wide survival analysis using a Cox proportional hazards model in a longitudinal cohort of 450 Chinese patients with PD, and further explored the functional effect of the target variant. Additionally, we built a clinical-genetic model by incorporating clinical characteristics and polygenic risk score (PRS) to predict cognitive decline in PD. RESULTS The cohort was followed up for an average of 5.25 (SE = 2.46) years, with 95 incidents of cognitive impairment. We identified significant association between locus rs75819919 (DPP6) and accelerated cognitive decline (p = 8.63E-09, beta = 1.74, SE = 0.30). Dual-luciferase reporter assay suggested this locus might be involved in the regulation of DPP6 expression. Using data set from the UK Biobank, we identified rs75819919 was associated with cognitive performance in the general population. Incorporation of PRS increased the model's predictability, achieving an average AUC of 75.6% through fivefold cross-validation in 1 000 iterations. CONCLUSIONS These findings improve the current understanding of the genetic etiology of cognitive impairment in PD, and provide a novel target DPP6 to explore therapeutic options. Our results also demonstrate the potential to develop clinical-genetic model to identify patients susceptible to cognitive impairment and thus provide personalized clinical guidance.
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Affiliation(s)
- Chunyu Li
- Laboratory of Neurodegenerative Disorders, Department of Neurology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Yanbing Hou
- Laboratory of Neurodegenerative Disorders, Department of Neurology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Ruwei Ou
- Laboratory of Neurodegenerative Disorders, Department of Neurology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Qianqian Wei
- Laboratory of Neurodegenerative Disorders, Department of Neurology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Lingyu Zhang
- Laboratory of Neurodegenerative Disorders, Department of Neurology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Kuncheng Liu
- Laboratory of Neurodegenerative Disorders, Department of Neurology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Junyu Lin
- Laboratory of Neurodegenerative Disorders, Department of Neurology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Xueping Chen
- Laboratory of Neurodegenerative Disorders, Department of Neurology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Wei Song
- Laboratory of Neurodegenerative Disorders, Department of Neurology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Bi Zhao
- Laboratory of Neurodegenerative Disorders, Department of Neurology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Ying Wu
- Laboratory of Neurodegenerative Disorders, Department of Neurology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Huifang Shang
- Laboratory of Neurodegenerative Disorders, Department of Neurology, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
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9
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Lott PC, Chiu K, Quino JE, Vang AP, Lloyd MW, Srivastava A, Chuang JH, Carvajal-Carmona LG. Development and Application of Genetic Ancestry Reconstruction Methods to Study Diversity of Patient-Derived Models in the NCI PDXNet Consortium. CANCER RESEARCH COMMUNICATIONS 2024; 4:2147-2152. [PMID: 39056190 PMCID: PMC11328913 DOI: 10.1158/2767-9764.crc-23-0417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 05/20/2024] [Accepted: 07/23/2024] [Indexed: 07/28/2024]
Abstract
Precision medicine holds great promise for improving cancer outcomes. Yet, there are large inequities in the demographics of patients from whom genomic data and models, including patient-derived xenografts (PDX), are developed and for whom treatments are optimized. In this study, we developed a genetic ancestry pipeline for the Cancer Genomics Cloud, which we used to assess the diversity of models currently available in the National Cancer Institute-supported PDX Development and Trial Centers Research Network (PDXNet). We showed that there is an under-representation of models derived from patients of non-European ancestry, consistent with other cancer model resources. We discussed these findings in the context of disparities in cancer incidence and outcomes among demographic groups in the US, as well as power analyses for biomarker discovery, to highlight the immediate need for developing models from minority populations to address cancer health equity in precision medicine. Our analyses identified key priority disparity-associated cancer types for which new models should be developed. SIGNIFICANCE Understanding whether and how tumor genetic factors drive differences in outcomes among U.S. minority groups is critical to addressing cancer health disparities. Our findings suggest that many additional models will be necessary to understand the genome-driven sources of these disparities.
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Affiliation(s)
- Paul C Lott
- The Health Equity Leadership, Science, and Community Research Laboratory, Genome Center, University of California, Davis, California
| | - Katherine Chiu
- The Health Equity Leadership, Science, and Community Research Laboratory, Genome Center, University of California, Davis, California
| | - Juanita Elizabeth Quino
- The Health Equity Leadership, Science, and Community Research Laboratory, Genome Center, University of California, Davis, California
| | - April Pangia Vang
- The Health Equity Leadership, Science, and Community Research Laboratory, Genome Center, University of California, Davis, California
| | - Michael W Lloyd
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, Maine
| | - Anuj Srivastava
- The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut
| | - Jeffrey H Chuang
- The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut
| | - Luis G Carvajal-Carmona
- The Health Equity Leadership, Science, and Community Research Laboratory, Genome Center, University of California, Davis, California
- Department of Biochemistry and Molecular Medicine, School of Medicine, University of California, Davis, California
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10
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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.
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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.
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11
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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.
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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.
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12
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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.
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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
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13
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Wang M, Chen H, Luo L, Huang Y, Duan S, Yuan H, Tang R, Liu C, He G. Forensic investigative genetic genealogy: expanding pedigree tracing and genetic inquiry in the genomic era. J Genet Genomics 2024:S1673-8527(24)00158-9. [PMID: 38969261 DOI: 10.1016/j.jgg.2024.06.016] [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: 04/25/2024] [Revised: 06/23/2024] [Accepted: 06/24/2024] [Indexed: 07/07/2024]
Abstract
Genetic genealogy provides crucial insights into the complex biological relationships within contemporary and ancient human populations by analyzing shared alleles and chromosomal segments that are identical by descent to understand kinship, migration patterns, and population dynamics. Within forensic science, forensic investigative genetic genealogy (FIGG) has gained prominence by leveraging next-generation sequencing technologies and population-specific genomic resources, opening new investigative avenues. In this review, we synthesize current knowledge, underscore recent advancements, and discuss the growing role of FIGG in forensic genomics. FIGG has been pivotal in revitalizing dormant inquiries and offering new genetic leads in numerous cold cases. Its effectiveness relies on the extensive single-nucleotide polymorphism profiles contributed by individuals from diverse populations to specialized genomic databases. Advances in computational genomics and the growth of human genomic databases have spurred a profound shift in the application of genetic genealogy across forensics, anthropology, and ancient DNA studies. As the field progresses, FIGG is evolving from a nascent practice into a more sophisticated and specialized discipline, shaping the future of forensic investigations.
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Affiliation(s)
- Mengge Wang
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, Sichuan 610041, China; Center for Archaeological Science, Sichuan University, Chengdu, Sichuan 610041, China; Anti-Drug Technology Center of Guangdong Province, Guangzhou, Guangdong 510000, China.
| | - Hongyu Chen
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, Sichuan 610041, China; Center for Archaeological Science, Sichuan University, Chengdu, Sichuan 610041, China; Department of Forensic Medicine, College of Basic Medicine, Chongqing Medical University, Chongqing 400016, China
| | - Lintao Luo
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, Sichuan 610041, China; Center for Archaeological Science, Sichuan University, Chengdu, Sichuan 610041, China; Department of Forensic Medicine, College of Basic Medicine, Chongqing Medical University, Chongqing 400016, China
| | - Yuguo Huang
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, Sichuan 610041, China; Center for Archaeological Science, Sichuan University, Chengdu, Sichuan 610041, China
| | - Shuhan Duan
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, Sichuan 610041, China
| | - Huijun Yuan
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, Sichuan 610041, China; Center for Archaeological Science, Sichuan University, Chengdu, Sichuan 610041, China.
| | - Renkuan Tang
- Department of Forensic Medicine, College of Basic Medicine, Chongqing Medical University, Chongqing 400016, China.
| | - Chao Liu
- Anti-Drug Technology Center of Guangdong Province, Guangzhou, Guangdong 510000, China.
| | - Guanglin He
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, Sichuan 610041, China; Center for Archaeological Science, Sichuan University, Chengdu, Sichuan 610041, China; Anti-Drug Technology Center of Guangdong Province, Guangzhou, Guangdong 510000, China.
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14
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Khalaf-Nazzal R, Dweikat I, Ubeyratna N, Fasham J, Alawneh M, Leslie J, Maree M, Gunning A, Zayed DZ, Voutsina N, McGavin L, Sawafta R, Owens M, Baker W, Turnpenny P, Al-Hijawi F, Baple EL, Crosby AH, Rawlins LE. TECPR2-related hereditary sensory and autonomic neuropathy in two siblings from Palestine. Am J Med Genet A 2024; 194:e63579. [PMID: 38436550 DOI: 10.1002/ajmg.a.63579] [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: 10/11/2023] [Revised: 01/05/2024] [Accepted: 02/17/2024] [Indexed: 03/05/2024]
Abstract
Due to the majority of currently available genome data deriving from individuals of European ancestry, the clinical interpretation of genomic variants in individuals from diverse ethnic backgrounds remains a major diagnostic challenge. Here, we investigated the genetic cause of a complex neurodevelopmental phenotype in two Palestinian siblings. Whole exome sequencing identified a homozygous missense TECPR2 variant (Chr14(GRCh38):g.102425085G>A; NM_014844.5:c.745G>A, p.(Gly249Arg)) absent in gnomAD, segregating appropriately with the inheritance pattern in the family. Variant assessment with in silico pathogenicity prediction and protein modeling tools alongside population database frequencies led to classification as a variant of uncertain significance. As pathogenic TECPR2 variants are associated with hereditary sensory and autonomic neuropathy with intellectual disability, we reviewed previously published candidate TECPR2 missense variants to clarify clinical outcomes and variant classification using current approved guidelines, classifying a number of published variants as of uncertain significance. This work highlights genomic healthcare inequalities and the challenges in interpreting rare genetic variants in populations underrepresented in genomic databases. It also improves understanding of the clinical and genetic spectrum of TECPR2-related neuropathy and contributes to addressing genomic data disparity and inequalities of the genomic architecture in Palestinian populations.
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Affiliation(s)
- Reham Khalaf-Nazzal
- Faculty of Medicine, Arab American University of Palestine, Jenin, Palestine
| | - Imad Dweikat
- Faculty of Medicine, Arab American University of Palestine, Jenin, Palestine
| | - Nishanka Ubeyratna
- RILD Wellcome Wolfson Medical Research Centre, Royal Devon University Hospitals NHS Foundation Trust, University of Exeter Medical School, Exeter, UK
| | - James Fasham
- RILD Wellcome Wolfson Medical Research Centre, Royal Devon University Hospitals NHS Foundation Trust, University of Exeter Medical School, Exeter, UK
- Peninsula Clinical Genetics Service, Royal Devon & Exeter Hospital (Heavitree), Exeter, UK
| | - Maysa Alawneh
- Department of Medicine, College of Medicine and Health Sciences, An-Najah National University, Nablus, Palestine
- Paediatric Department, An-Najah National University Hospital, Nablus, Palestine
| | - Joseph Leslie
- RILD Wellcome Wolfson Medical Research Centre, Royal Devon University Hospitals NHS Foundation Trust, University of Exeter Medical School, Exeter, UK
| | - Mosab Maree
- Department of Medicine, College of Medicine and Health Sciences, An-Najah National University, Nablus, Palestine
| | - Adam Gunning
- RILD Wellcome Wolfson Medical Research Centre, Royal Devon University Hospitals NHS Foundation Trust, University of Exeter Medical School, Exeter, UK
| | - Deyala Z Zayed
- Paediatric Department, An-Najah National University Hospital, Nablus, Palestine
| | - Nikol Voutsina
- RILD Wellcome Wolfson Medical Research Centre, Royal Devon University Hospitals NHS Foundation Trust, University of Exeter Medical School, Exeter, UK
| | - Lucy McGavin
- University Hospitals Plymouth NHS Trust, Plymouth, UK
- University of Plymouth, Plymouth, UK
| | - Reem Sawafta
- Paediatric Department, An-Najah National University Hospital, Nablus, Palestine
| | - Martina Owens
- RILD Wellcome Wolfson Medical Research Centre, Royal Devon University Hospitals NHS Foundation Trust, University of Exeter Medical School, Exeter, UK
| | - Wisam Baker
- Paediatric Department, Dr. Khalil Suleiman Government Hospital, Jenin, Palestine
| | - Peter Turnpenny
- Peninsula Clinical Genetics Service, Royal Devon & Exeter Hospital (Heavitree), Exeter, UK
| | - Fida' Al-Hijawi
- Paediatric Community Outpatient Clinics, Palestinian Ministry of Health, Jenin, Palestine
| | - Emma L Baple
- RILD Wellcome Wolfson Medical Research Centre, Royal Devon University Hospitals NHS Foundation Trust, University of Exeter Medical School, Exeter, UK
- Peninsula Clinical Genetics Service, Royal Devon & Exeter Hospital (Heavitree), Exeter, UK
| | - Andrew H Crosby
- RILD Wellcome Wolfson Medical Research Centre, Royal Devon University Hospitals NHS Foundation Trust, University of Exeter Medical School, Exeter, UK
| | - Lettie E Rawlins
- RILD Wellcome Wolfson Medical Research Centre, Royal Devon University Hospitals NHS Foundation Trust, University of Exeter Medical School, Exeter, UK
- Peninsula Clinical Genetics Service, Royal Devon & Exeter Hospital (Heavitree), Exeter, UK
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15
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Sun KY, Bai X, Chen S, Bao S, Zhang C, Kapoor M, Backman J, Joseph T, Maxwell E, Mitra G, Gorovits A, Mansfield A, Boutkov B, Gokhale S, Habegger L, Marcketta A, Locke AE, Ganel L, Hawes A, Kessler MD, Sharma D, Staples J, Bovijn J, Gelfman S, Di Gioia A, Rajagopal VM, Lopez A, Varela JR, Alegre-Díaz J, Berumen J, Tapia-Conyer R, Kuri-Morales P, Torres J, Emberson J, Collins R, Cantor M, Thornton T, Kang HM, Overton JD, Shuldiner AR, Cremona ML, Nafde M, Baras A, Abecasis G, Marchini J, Reid JG, Salerno W, Balasubramanian S. A deep catalogue of protein-coding variation in 983,578 individuals. Nature 2024; 631:583-592. [PMID: 38768635 PMCID: PMC11254753 DOI: 10.1038/s41586-024-07556-0] [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: 06/19/2023] [Accepted: 05/10/2024] [Indexed: 05/22/2024]
Abstract
Rare coding variants that substantially affect function provide insights into the biology of a gene1-3. However, ascertaining the frequency of such variants requires large sample sizes4-8. Here we present a catalogue of human protein-coding variation, derived from exome sequencing of 983,578 individuals across diverse populations. In total, 23% of the Regeneron Genetics Center Million Exome (RGC-ME) data come from individuals of African, East Asian, Indigenous American, Middle Eastern and South Asian ancestry. The catalogue includes more than 10.4 million missense and 1.1 million predicted loss-of-function (pLOF) variants. We identify individuals with rare biallelic pLOF variants in 4,848 genes, 1,751 of which have not been previously reported. From precise quantitative estimates of selection against heterozygous loss of function (LOF), we identify 3,988 LOF-intolerant genes, including 86 that were previously assessed as tolerant and 1,153 that lack established disease annotation. We also define regions of missense depletion at high resolution. Notably, 1,482 genes have regions that are depleted of missense variants despite being tolerant of pLOF variants. Finally, we estimate that 3% of individuals have a clinically actionable genetic variant, and that 11,773 variants reported in ClinVar with unknown significance are likely to be deleterious cryptic splice sites. To facilitate variant interpretation and genetics-informed precision medicine, we make this resource of coding variation from the RGC-ME dataset publicly accessible through a variant allele frequency browser.
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Affiliation(s)
| | | | - Siying Chen
- Regeneron Genetics Center, Tarrytown, NY, USA
| | - Suying Bao
- Regeneron Genetics Center, Tarrytown, NY, USA
| | | | | | | | | | | | | | | | | | | | | | | | | | | | - Liron Ganel
- Regeneron Genetics Center, Tarrytown, NY, USA
| | | | | | | | | | | | | | | | | | | | | | - Jesús Alegre-Díaz
- Faculty of Medicine, National Autonomous University of Mexico (UNAM), Mexico City, Mexico
| | - Jaime Berumen
- Faculty of Medicine, National Autonomous University of Mexico (UNAM), Mexico City, Mexico
| | - Roberto Tapia-Conyer
- Faculty of Medicine, National Autonomous University of Mexico (UNAM), Mexico City, Mexico
| | - Pablo Kuri-Morales
- Faculty of Medicine, National Autonomous University of Mexico (UNAM), Mexico City, Mexico
- Instituto Tecnológico y de Estudios Superiores de Monterrey, Monterrey, Mexico
| | - Jason Torres
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Jonathan Emberson
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Rory Collins
- Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | | | | | | | | | | | | | - Mona Nafde
- Regeneron Genetics Center, Tarrytown, NY, USA
| | - Aris Baras
- Regeneron Genetics Center, Tarrytown, NY, USA
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16
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Hong EP, Lim SH, Youn DH, Han SW, Jung H, Lee JJ, Jeon JP. Longitudinal Genome-Wide Association Study of Cognitive Impairment after Subarachnoid Hemorrhage. Biomedicines 2024; 12:1387. [PMID: 39061961 PMCID: PMC11275094 DOI: 10.3390/biomedicines12071387] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2024] [Revised: 06/06/2024] [Accepted: 06/19/2024] [Indexed: 07/28/2024] Open
Abstract
OBJECTIVES The occurrence of cognitive deficits after subarachnoid hemorrhage (SAH) is highly possible, leading to vascular dementia. We performed a novel longitudinal genome-wide association study (GWAS) to identify genetic modifications associated with cognitive impairment following SAH in a long-term prospective cohort study. MATERIALS AND METHODS This GWAS involved 153 patients with SAH sharing 5,971,372 markers after high-throughput imputation. Genome-wide Cox proportional hazard regression testing was performed to estimate the hazard ratio (HR) and 95% confidence interval (CI). Subsequently, a weighted polygenetic risk score (wPRS) was determined, based on GWAS-driven loci and risk stratification. RESULTS Cognitive impairment was observed in 65 patients (42.5%) during a mean follow-up of 37.7 ± 12.4 months. Five genome-wide signals, including rs138753053 (PDCD6IP-LOC101928135, HR = 28.33, p = 3.4 × 10-8), rs56823384 (LINC00499, HR = 12.47, p = 2.8 × 10-9), rs145397166 (CASC15, HR = 11.16, p = 1.7 × 10-8), rs10503670 (LPL-SLC18A1, HR = 2.88, p = 4.0 × 10-8), and rs76507772 (IRS2, HR = 5.99, p = 3.5 × 10-8), were significantly associated with cognitive impairment following SAH. In addition, the well-constructed wPRS containing five markers showed nominal ability to predict cognitive impairment (AUROC = 0.745, 95% CI: 0.667-0.824). Tertile stratification showed a higher effectiveness in predicting cognitive impairment, especially in those with haptoglobin 2-1 (HR = 44.59, 95% CI: 8.61-231.08). CONCLUSIONS Our study revealed novel susceptible loci for cognitive impairment, longitudinally measured in patients with SAH. The clinical utility of these loci will be evaluated in further follow-up studies.
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Affiliation(s)
- Eun Pyo Hong
- Institute of New Frontier Research, Hallym University College of Medicine, Chuncheon 24254, Republic of Korea; (E.P.H.); (S.H.L.); (D.H.Y.); (S.W.H.); (H.J.)
| | - Seung Hyuk Lim
- Institute of New Frontier Research, Hallym University College of Medicine, Chuncheon 24254, Republic of Korea; (E.P.H.); (S.H.L.); (D.H.Y.); (S.W.H.); (H.J.)
| | - Dong Hyuk Youn
- Institute of New Frontier Research, Hallym University College of Medicine, Chuncheon 24254, Republic of Korea; (E.P.H.); (S.H.L.); (D.H.Y.); (S.W.H.); (H.J.)
| | - Sung Woo Han
- Institute of New Frontier Research, Hallym University College of Medicine, Chuncheon 24254, Republic of Korea; (E.P.H.); (S.H.L.); (D.H.Y.); (S.W.H.); (H.J.)
| | - Harry Jung
- Institute of New Frontier Research, Hallym University College of Medicine, Chuncheon 24254, Republic of Korea; (E.P.H.); (S.H.L.); (D.H.Y.); (S.W.H.); (H.J.)
| | - Jae Jun Lee
- Institute of New Frontier Research, Hallym University College of Medicine, Chuncheon 24254, Republic of Korea; (E.P.H.); (S.H.L.); (D.H.Y.); (S.W.H.); (H.J.)
- Department of Anesthesiology and Pain Medicine, Hallym University College of Medicine, Chuncheon 24253, Republic of Korea
| | - Jin Pyeong Jeon
- Department of Neurosurgery, Hallym University College of Medicine, 77 Sakju-ro, Chuncheon 24253, Republic of Korea
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Martin BE, Sands T, Bier L, Bergner A, Boehme AK, Lippa N. Comparing the frequency of variants of uncertain significance (VUS) between ancestry groups in a paediatric epilepsy cohort. J Med Genet 2024; 61:645-651. [PMID: 38453479 DOI: 10.1136/jmg-2023-109450] [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: 06/30/2023] [Accepted: 02/21/2024] [Indexed: 03/09/2024]
Abstract
BACKGROUND Studies indicate that variants of uncertain significance are more common in non-European populations due to lack of a diversity in population databases. This difference has not been explored in epilepsy, which is increasingly found to be genetic in paediatric populations, and has precision medicine applications. This study examines the differences in the frequency of uncertain next-generation sequencing (NGS) results among a paediatric epilepsy cohort between ancestral groups historically under-represented in biomedical research (UBR) and represented in biomedical research (RBR). METHODS A retrospective chart review of patients with epilepsy seen at Columbia University Irving Medical Center (CUIMC). One hundred seventy-eight cases met the following criteria: (1) visited any provider within the Pediatric Neurology Clinic at CUIMC, (2) had an ICD code indicating a diagnosis of epilepsy, (3) underwent NGS testing after March 2015 and (4) had self-reported ancestry that fit into a single dichotomous category of either historically represented or under-represented in biomedical research. RESULTS UBR cases had significantly higher rates of uncertain results when compared with RBR cases (79.2% UBR, 20.8% RBR; p value=0.002). This finding remained true after controlling for potential confounding factors, including sex, intellectual disability or developmental delay, epilepsy type, age of onset, number of genes tested and year of testing. CONCLUSION Our results add to the literature that individuals who are of ancestries historically under-represented in genetics research are more likely to receive uncertain genetic results than those of represented majority ancestral groups and establishes this finding in an epilepsy cohort.
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Affiliation(s)
- Bree E Martin
- Department of General Pediatrics, Boston Children's Hospital, Boston, Massachusetts, USA
| | - Tristan Sands
- Department of Neurology, Columbia University, New York, New York, USA
- Columbia University Irving Medical Center, New York, New York, USA
| | - Louise Bier
- Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Amanda Bergner
- Genetic Counseling Graduate Program, Columbia University Vagelos College of Physicians and Surgeons, New York, New York, USA
- Department of Genetics and Development, Columbia University Vagelos College of Physicians and Surgeons, New York, New York, USA
| | - Amelia K Boehme
- Department of Neurology, Columbia University, New York, New York, USA
| | - Natalie Lippa
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, New York, USA
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18
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Jiang T, Guo H, Liu Y, Li G, Cui Z, Cui X, Liu Y, Li Y, Zhang A, Cao S, Zhao T, Juan L, Kong W, Chen M, Liu D, Liu H, Zhang Y, Xu K, Wang Y, He M, Guo J, Lu M, Chen J, Zhao X, Zhao G, Dang S, Chen C, Wu X, Qin Q, Li Y, Shen H, Jin L, Liu B, Chen X, Zhao Y, Wang Y. A comprehensive genetic variant reference for the Chinese population. Sci Bull (Beijing) 2024:S2095-9273(24)00442-0. [PMID: 38945749 DOI: 10.1016/j.scib.2024.06.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 03/07/2024] [Accepted: 04/28/2024] [Indexed: 07/02/2024]
Affiliation(s)
- Tao Jiang
- Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China; Zhengzhou Research Institute, Harbin Institute of Technology, Zhengzhou 450000, China
| | - Hongzhe Guo
- Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China; Zhengzhou Research Institute, Harbin Institute of Technology, Zhengzhou 450000, China
| | - Yadong Liu
- Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China; Zhengzhou Research Institute, Harbin Institute of Technology, Zhengzhou 450000, China
| | - Gaoyang Li
- Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China
| | - Zhe Cui
- Harbin Nebula Bioinformatics Technology Company, Harbin 150001, China
| | - Xinran Cui
- Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China
| | - Yue Liu
- Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China
| | - Yang Li
- Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China
| | - Anqi Zhang
- Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China
| | - Shuqi Cao
- Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China
| | - Tianyi Zhao
- Zhengzhou Research Institute, Harbin Institute of Technology, Zhengzhou 450000, China; School of Medicine and Health, Harbin Institute of Technology, Harbin 150001, China
| | - Liran Juan
- School of Medicine and Health, Harbin Institute of Technology, Harbin 150001, China
| | - Weize Kong
- Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China
| | - Ming Chen
- Harbin Nebula Bioinformatics Technology Company, Harbin 150001, China
| | - Dianming Liu
- Harbin Nebula Bioinformatics Technology Company, Harbin 150001, China
| | - Hongri Liu
- Harbin Nebula Bioinformatics Technology Company, Harbin 150001, China
| | - Yixiao Zhang
- Department of Urology Surgery, Key Laboratory of Precision Medical Research on Major Chronic Disease, Liaoning Province, Shengjing Hospital of China Medical University, Shenyang 110004, China
| | - Kelin Xu
- Fudan University Taizhou Institute of Health Sciences, Taizhou 200438, China; Department of Biostatistics, School of Public Health, Fudan University, Shanghai 200433, China
| | - Yongjun Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China; China National Clinical Research Center for Neurological Diseases, Beijing 100070, China
| | - Meian He
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Jiancheng Guo
- Henan Research Center for Genomic Sequencing and Translational Medicine, Zhengzhou University, Zhengzhou 450001, China; The Second Affiliated Hospital of Zhengzhou University, Zhengzhou 450014, China
| | - Ming Lu
- Clinical Epidemiology Unit, Qilu Hospital of Shandong University, Jinan 250012, China
| | - Jun Chen
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou 350001, China
| | - Xing Zhao
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China
| | - Genming Zhao
- School of Public Health, Fudan University, Shanghai 200433, China
| | - Shaonong Dang
- School of Public Health, Xi'an Jiaotong University, Xi'an 710061, China
| | - Chao Chen
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha 410083, China
| | - Xiaojian Wu
- Department of Colorectal Surgery, the Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, China; Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Sun Yat-sen University, Guangzhou 510655, China
| | - Qiyuan Qin
- Department of Colorectal Surgery, the Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, China; Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Sun Yat-sen University, Guangzhou 510655, China
| | - Yixue Li
- Guangzhou Laboratory, Guangzhou 510005, China
| | - Hongbing Shen
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Li Jin
- Fudan University Taizhou Institute of Health Sciences, Taizhou 200438, China; State Key Laboratory of Genetic Engineering, Human Phenome Institute, and School of Life Sciences, Fudan University, Shanghai 200433, China
| | - Bo Liu
- Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China; Zhengzhou Research Institute, Harbin Institute of Technology, Zhengzhou 450000, China.
| | - Xingdong Chen
- Fudan University Taizhou Institute of Health Sciences, Taizhou 200438, China; State Key Laboratory of Genetic Engineering, Human Phenome Institute, and School of Life Sciences, Fudan University, Shanghai 200433, China.
| | - Yuhong Zhao
- Department of Clinical Epidemiology, Clinical Research Center, Shengjing Hospital of China Medical University, Shenyang 110004, China.
| | - Yadong Wang
- Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China; Zhengzhou Research Institute, Harbin Institute of Technology, Zhengzhou 450000, China; School of Medicine and Health, Harbin Institute of Technology, Harbin 150001, China.
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19
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Su H, Wang M, Li X, Duan S, Sun Q, Sun Y, Wang Z, Yang Q, Huang Y, Zhong J, Chen J, Jiang X, Ma J, Yang T, Liu Y, Luo L, Liu Y, Yang J, Chen G, Liu C, Cai Y, He G. Population genetic admixture and evolutionary history in the Shandong Peninsula inferred from integrative modern and ancient genomic resources. BMC Genomics 2024; 25:611. [PMID: 38890579 PMCID: PMC11184692 DOI: 10.1186/s12864-024-10514-9] [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: 03/15/2024] [Accepted: 06/11/2024] [Indexed: 06/20/2024] Open
Abstract
BACKGROUND Ancient northern East Asians (ANEA) from the Yellow River region, who pioneered millet cultivation, play a crucial role in understanding the origins of ethnolinguistically diverse populations in modern China and the entire landscape of deep genetic structure and variation discovery in modern East Asians. However, the direct links between ANEA and geographically proximate modern populations, as well as the biological adaptive processes involved, remain poorly understood. RESULTS Here, we generated genome-wide SNP data for 264 individuals from geographically different Han populations in Shandong. An integrated genomic resource encompassing both modern and ancient East Asians was compiled to examine fine-scale population admixture scenarios and adaptive traits. The reconstruction of demographic history and hierarchical clustering patterns revealed that individuals from the Shandong Peninsula share a close genetic affinity with ANEA, indicating long-term genetic continuity and mobility in the lower Yellow River basin since the early Neolithic period. Biological adaptive signatures, including those related to immune and metabolic pathways, were identified through analyses of haplotype homozygosity and allele frequency spectra. These signatures are linked to complex traits such as height and body mass index, which may be associated with adaptations to cold environments, dietary practices, and pathogen exposure. Additionally, allele frequency trajectories over time and a haplotype network of two highly differentiated genes, ABCC11 and SLC10A1, were delineated. These genes, which are associated with axillary odor and bilirubin metabolism, respectively, illustrate how local adaptations can influence the diversification of traits in East Asians. CONCLUSIONS Our findings provide a comprehensive genomic dataset that elucidates the fine-scale genetic history and evolutionary trajectory of natural selection signals and disease susceptibility in Han Chinese populations. This study serves as a paradigm for integrating spatiotemporally diverse ancient genomes in the era of population genomic medicine.
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Affiliation(s)
- Haoran Su
- Genetic and Prenatal Diagnosis Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637007, Sichuan, China
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- School of Laboratory Medicine, North Sichuan Medical College, Nanchong, 637007, Sichuan, China
| | - Mengge Wang
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China.
- Center for Archaeological Science, Sichuan University, Chengdu, 610000, China.
- Research Center for Genomic Medicine, North Sichuan Medical College, Nanchong, 637100, China.
| | - Xiangping Li
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- School of Forensic Medicine, Kunming Medical University, Kunming, 650500, China
| | - Shuhan Duan
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- Research Center for Genomic Medicine, North Sichuan Medical College, Nanchong, 637100, China
- Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College and Genetic and Prenatal Diagnosis Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637007, Sichuan, China
| | - Qiuxia Sun
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- Department of Forensic Medicine, College of Basic Medicine, Chongqing Medical University, Chongqing, 400331, China
| | - Yuntao Sun
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- West China School of Basic Science & Forensic Medicine, Sichuan University, Chengdu, 610041, China
| | - Zhiyong Wang
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- School of Forensic Medicine, Kunming Medical University, Kunming, 650500, China
| | - Qingxin Yang
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- School of Forensic Medicine, Kunming Medical University, Kunming, 650500, China
| | - Yuguo Huang
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
| | - Jie Zhong
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
| | - Jing Chen
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, 030001, China
| | - Xiucheng Jiang
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- Research Center for Genomic Medicine, North Sichuan Medical College, Nanchong, 637100, China
- Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College and Genetic and Prenatal Diagnosis Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637007, Sichuan, China
| | - Jinyue Ma
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- Research Center for Genomic Medicine, North Sichuan Medical College, Nanchong, 637100, China
- Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College and Genetic and Prenatal Diagnosis Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637007, Sichuan, China
| | - Ting Yang
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- School of Forensic Medicine, Kunming Medical University, Kunming, 650500, China
| | - Yunhui Liu
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- Department of Forensic Medicine, College of Basic Medicine, Chongqing Medical University, Chongqing, 400331, China
| | - Lintao Luo
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- Department of Forensic Medicine, College of Basic Medicine, Chongqing Medical University, Chongqing, 400331, China
| | - Yan Liu
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China
- Research Center for Genomic Medicine, North Sichuan Medical College, Nanchong, 637100, China
- Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College and Genetic and Prenatal Diagnosis Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637007, Sichuan, China
| | - Junbao Yang
- Research Center for Genomic Medicine, North Sichuan Medical College, Nanchong, 637100, China
- Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College and Genetic and Prenatal Diagnosis Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637007, Sichuan, China
| | - Gang Chen
- Hunan Key Laboratory of Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha, 410075, China
| | - Chao Liu
- Anti-Drug Technology Center of Guangdong Province, Guangzhou, 510230, China.
| | - Yan Cai
- Genetic and Prenatal Diagnosis Center, Affiliated Hospital of North Sichuan Medical College, Nanchong, 637007, Sichuan, China.
| | - Guanglin He
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610000, China.
- Center for Archaeological Science, Sichuan University, Chengdu, 610000, China.
- Research Center for Genomic Medicine, North Sichuan Medical College, Nanchong, 637100, China.
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20
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He Y, Lei C, Wan C, Zeng S, Zhang T, Luo F, Li R, Li X, Zhao A, Xiao D, Luo Y, Shan K, Qi X, Jin X. A comprehensive whole genome database of ethnic minority populations. Sci Rep 2024; 14:13954. [PMID: 38886537 PMCID: PMC11183174 DOI: 10.1038/s41598-024-63892-1] [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: 11/28/2023] [Accepted: 06/03/2024] [Indexed: 06/20/2024] Open
Abstract
China, is characterized by its remarkable ethnical diversity, which necessitates whole genome variation data from multiple populations as crucial tools for advancing population genetics and precision medical research. However, there has been a scarcity of research concentrating on the whole genome of ethnic minority groups. To fill this gap, we developed the Guizhou Multi-ethnic Genome Database (GMGD). It comprises whole genome sequencing data from 476 healthy unrelated individuals spanning 11 ethnic minorities groups in Guizhou Province, Southwest China, including Bouyei, Dong, Miao, Yi, Bai, Gelo, Zhuang, Tujia, Yao, Hui, and Sui. The GMGD database comprises more than 16.33 million variants in GRCh38 and 16.20 million variants in GRCh37. Among these, approximately 11.9% (1,956,322) of the variants in GRCh38 and 18.5% (3,009,431) of the variants in GRCh37 are entirely new and do not exist in the dbSNP database. These novel variants shed light on the genetic diversity landscape across these populations, providing valuable insights with an average coverage of 5.5 ×. This makes GMGD the largest genome-wide database encompassing the most diverse ethnic groups to date. The GMGD interactive interface facilitates researchers with multi-dimensional mutation search methods and displays population frequency differences among global populations. Furthermore, GMGD is equipped with a genotype-imputation function, enabling enhanced capabilities for low-depth genomic research or targeted region capture studies. GMGD offers unique insights into the genomic variation landscape of different ethnic groups, which are freely accessible at https://db.cngb.org/pop/gmgd/ .
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Affiliation(s)
- Yan He
- Key Laboratory of Endemic and Ethnic Diseases, Ministry of Education and Key Laboratory of Medical Molecular Biology of Guizhou Province, Collaborative Innovation Center for Prevention and Control of Endemic and Ethnic Regional Diseases Co-constructed by the Province and Ministry, Guizhou Medical University, Guiyang, 550004, Guizhou, China
| | - Changgui Lei
- BGI Research, Shenzhen, 518083, China
- BGI Research, Guiyang, 550000, China
- BGI Research, Wuhan, 430074, China
| | - Chanjuan Wan
- Key Laboratory of Endemic and Ethnic Diseases, Ministry of Education and Key Laboratory of Medical Molecular Biology of Guizhou Province, Collaborative Innovation Center for Prevention and Control of Endemic and Ethnic Regional Diseases Co-constructed by the Province and Ministry, Guizhou Medical University, Guiyang, 550004, Guizhou, China
| | - Shuang Zeng
- Key Laboratory of Endemic and Ethnic Diseases, Ministry of Education and Key Laboratory of Medical Molecular Biology of Guizhou Province, Collaborative Innovation Center for Prevention and Control of Endemic and Ethnic Regional Diseases Co-constructed by the Province and Ministry, Guizhou Medical University, Guiyang, 550004, Guizhou, China
- BGI Research, Shenzhen, 518083, China
- BGI Research, Guiyang, 550000, China
- BGI Research, Wuhan, 430074, China
| | - Ting Zhang
- Key Laboratory of Endemic and Ethnic Diseases, Ministry of Education and Key Laboratory of Medical Molecular Biology of Guizhou Province, Collaborative Innovation Center for Prevention and Control of Endemic and Ethnic Regional Diseases Co-constructed by the Province and Ministry, Guizhou Medical University, Guiyang, 550004, Guizhou, China
| | - Fei Luo
- BGI Research, Shenzhen, 518083, China
- BGI Research, Guiyang, 550000, China
- BGI Research, Wuhan, 430074, China
| | - Ruichao Li
- Key Laboratory of Endemic and Ethnic Diseases, Ministry of Education and Key Laboratory of Medical Molecular Biology of Guizhou Province, Collaborative Innovation Center for Prevention and Control of Endemic and Ethnic Regional Diseases Co-constructed by the Province and Ministry, Guizhou Medical University, Guiyang, 550004, Guizhou, China
| | - Xiaokun Li
- BGI Research, Shenzhen, 518083, China
- BGI Research, Guiyang, 550000, China
| | - Anshu Zhao
- Key Laboratory of Endemic and Ethnic Diseases, Ministry of Education and Key Laboratory of Medical Molecular Biology of Guizhou Province, Collaborative Innovation Center for Prevention and Control of Endemic and Ethnic Regional Diseases Co-constructed by the Province and Ministry, Guizhou Medical University, Guiyang, 550004, Guizhou, China
| | - Defu Xiao
- BGI Research, Shenzhen, 518083, China
- BGI Research, Guiyang, 550000, China
| | - Yunyan Luo
- Key Laboratory of Endemic and Ethnic Diseases, Ministry of Education and Key Laboratory of Medical Molecular Biology of Guizhou Province, Collaborative Innovation Center for Prevention and Control of Endemic and Ethnic Regional Diseases Co-constructed by the Province and Ministry, Guizhou Medical University, Guiyang, 550004, Guizhou, China
- BGI Research, Guiyang, 550000, China
| | - Keren Shan
- Key Laboratory of Endemic and Ethnic Diseases, Ministry of Education and Key Laboratory of Medical Molecular Biology of Guizhou Province, Collaborative Innovation Center for Prevention and Control of Endemic and Ethnic Regional Diseases Co-constructed by the Province and Ministry, Guizhou Medical University, Guiyang, 550004, Guizhou, China
| | - Xiaolan Qi
- Key Laboratory of Endemic and Ethnic Diseases, Ministry of Education and Key Laboratory of Medical Molecular Biology of Guizhou Province, Collaborative Innovation Center for Prevention and Control of Endemic and Ethnic Regional Diseases Co-constructed by the Province and Ministry, Guizhou Medical University, Guiyang, 550004, Guizhou, China.
| | - Xin Jin
- BGI Research, Shenzhen, 518083, China.
- BGI Research, Guiyang, 550000, China.
- Shenzhen Key Laboratory of Transomics Biotechnologies, BGI Research, Shenzhen, China.
- School of Medicine, South China University of Technology, Guangzhou, China.
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21
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Ardiansyah E, Riza AL, Dian S, Ganiem AR, Alisjahbana B, Setiabudiawan TP, van Laarhoven A, van Crevel R, Kumar V. Sequencing whole genomes of the West Javanese population in Indonesia reveals novel variants and improves imputation accuracy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.14.598981. [PMID: 38915501 PMCID: PMC11195206 DOI: 10.1101/2024.06.14.598981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
Existing genotype imputation reference panels are mainly derived from European populations, limiting their accuracy in non-European populations. To improve imputation accuracy for Indonesians, the world's fourth most populous country, we combined Whole Genome Sequencing (WGS) data from 227 West Javanese individuals with East Asian data from the 1000 Genomes Project. This created three reference panels: EAS 1KGP3 (EASp), Indonesian (INDp), and a combined panel (EASp+INDp). We also used ten West-Javanese samples with WGS and SNP-typing data for benchmarking. We identified 1.8 million novel single nucleotide variants (SNVs) in the West Javanese population, which, while similar to the East Asians, are distinct from the Central Indonesian Flores population. Adding INDp to the EASp reference panel improved imputation accuracy (R2) from 0.85 to 0.90, and concordance from 87.88% to 91.13%. These findings underscore the importance of including Indonesian genetic data in reference panels, advocating for broader WGS of diverse Indonesian populations to enhance genomic studies.
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Affiliation(s)
- Edwin Ardiansyah
- Research Center for Care and Control of Infectious Diseases, Universitas Padjadjaran, Bandung, Indonesia
| | - Anca-Lelia Riza
- Laboratory of Human Genomics, University of Medicine and Pharmacy of Craiova, 200638 Craiova, Romania
| | - Sofiati Dian
- Research Center for Care and Control of Infectious Diseases, Universitas Padjadjaran, Bandung, Indonesia
- Department of Neurology, Hasan Sadikin Hospital, Faculty of Medicine, Universitas Padjadjaran, Bandung, Indonesia
| | - Ahmad Rizal Ganiem
- Research Center for Care and Control of Infectious Diseases, Universitas Padjadjaran, Bandung, Indonesia
- Department of Neurology, Hasan Sadikin Hospital, Faculty of Medicine, Universitas Padjadjaran, Bandung, Indonesia
| | - Bachti Alisjahbana
- Research Center for Care and Control of Infectious Diseases, Universitas Padjadjaran, Bandung, Indonesia
- Department of Internal Medicine, Hasan Sadikin Hospital, Faculty of Medicine, Universitas Padjadjaran, Bandung, Indonesia
| | - Todia P Setiabudiawan
- Department of Internal Medicine and Radboud Center of Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, Netherlands
| | - Arjan van Laarhoven
- Department of Internal Medicine and Radboud Center of Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, Netherlands
| | - Reinout van Crevel
- Department of Internal Medicine and Radboud Center of Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, Netherlands
| | - Vinod Kumar
- Department of Internal Medicine and Radboud Center of Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, Netherlands
- University of Groningen, University Medical Center Groningen, department of Genetics, Groningen, the Netherlands
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22
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Chen R, Lukianova E, van der Loeff IS, Spegarova JS, Willet JDP, James KD, Ryder EJ, Griffin H, IJspeert H, Gajbhiye A, Lamoliatte F, Marin-Rubio JL, Woodbine L, Lemos H, Swan DJ, Pintar V, Sayes K, Ruiz-Morales ER, Eastham S, Dixon D, Prete M, Prigmore E, Jeggo P, Boyes J, Mellor A, Huang L, van der Burg M, Engelhardt KR, Stray-Pedersen A, Erichsen HC, Gennery AR, Trost M, Adams DJ, Anderson G, Lorenc A, Trynka G, Hambleton S. NUDCD3 deficiency disrupts V(D)J recombination to cause SCID and Omenn syndrome. Sci Immunol 2024; 9:eade5705. [PMID: 38787962 DOI: 10.1126/sciimmunol.ade5705] [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: 08/24/2022] [Accepted: 04/24/2024] [Indexed: 05/26/2024]
Abstract
Inborn errors of T cell development present a pediatric emergency in which timely curative therapy is informed by molecular diagnosis. In 11 affected patients across four consanguineous kindreds, we detected homozygosity for a single deleterious missense variant in the gene NudC domain-containing 3 (NUDCD3). Two infants had severe combined immunodeficiency with the complete absence of T and B cells (T -B- SCID), whereas nine showed classical features of Omenn syndrome (OS). Restricted antigen receptor gene usage by residual T lymphocytes suggested impaired V(D)J recombination. Patient cells showed reduced expression of NUDCD3 protein and diminished ability to support RAG-mediated recombination in vitro, which was associated with pathologic sequestration of RAG1 in the nucleoli. Although impaired V(D)J recombination in a mouse model bearing the homologous variant led to milder immunologic abnormalities, NUDCD3 is absolutely required for healthy T and B cell development in humans.
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Affiliation(s)
- Rui Chen
- Translational and Clinical Research Institute, Newcastle University, NE2 4HH Newcastle upon Tyne, UK
| | - Elena Lukianova
- Wellcome Sanger Institute, Wellcome Genome Campus, CB10 1SA Hinxton, UK
| | - Ina Schim van der Loeff
- Translational and Clinical Research Institute, Newcastle University, NE2 4HH Newcastle upon Tyne, UK
- Great North Children's Hospital, Newcastle upon Tyne Hospitals NHS Foundation Trust, NE1 4LP Newcastle upon Tyne, UK
| | | | - Joseph D P Willet
- Translational and Clinical Research Institute, Newcastle University, NE2 4HH Newcastle upon Tyne, UK
| | - Kieran D James
- Institute of Immunology and Immunotherapy, University of Birmingham. B15 2TT Birmingham, UK
| | - Edward J Ryder
- Wellcome Sanger Institute, Wellcome Genome Campus, CB10 1SA Hinxton, UK
| | - Helen Griffin
- Translational and Clinical Research Institute, Newcastle University, NE2 4HH Newcastle upon Tyne, UK
| | - Hanna IJspeert
- Department of Immunology, Erasmus University Medical Center, Rotterdam 3000 CA, Netherlands
| | - Akshada Gajbhiye
- Biosciences Institute, Newcastle University, NE2 4HH Newcastle upon Tyne, UK
| | - Frederic Lamoliatte
- Biosciences Institute, Newcastle University, NE2 4HH Newcastle upon Tyne, UK
| | - Jose L Marin-Rubio
- Biosciences Institute, Newcastle University, NE2 4HH Newcastle upon Tyne, UK
| | - Lisa Woodbine
- Genome Damage and Stability Centre, University of Sussex, BN1 9RQ Brighton, UK
| | - Henrique Lemos
- Translational and Clinical Research Institute, Newcastle University, NE2 4HH Newcastle upon Tyne, UK
| | - David J Swan
- Translational and Clinical Research Institute, Newcastle University, NE2 4HH Newcastle upon Tyne, UK
| | - Valeria Pintar
- Translational and Clinical Research Institute, Newcastle University, NE2 4HH Newcastle upon Tyne, UK
| | - Kamal Sayes
- Translational and Clinical Research Institute, Newcastle University, NE2 4HH Newcastle upon Tyne, UK
| | | | - Simon Eastham
- Wellcome Sanger Institute, Wellcome Genome Campus, CB10 1SA Hinxton, UK
| | - David Dixon
- Biosciences Institute, Newcastle University, NE2 4HH Newcastle upon Tyne, UK
| | - Martin Prete
- Wellcome Sanger Institute, Wellcome Genome Campus, CB10 1SA Hinxton, UK
| | - Elena Prigmore
- Wellcome Sanger Institute, Wellcome Genome Campus, CB10 1SA Hinxton, UK
| | - Penny Jeggo
- Genome Damage and Stability Centre, University of Sussex, BN1 9RQ Brighton, UK
| | - Joan Boyes
- Faculty of Biological Sciences, University of Leeds, LS2 9JT Leeds, UK
| | - Andrew Mellor
- Translational and Clinical Research Institute, Newcastle University, NE2 4HH Newcastle upon Tyne, UK
| | - Lei Huang
- Translational and Clinical Research Institute, Newcastle University, NE2 4HH Newcastle upon Tyne, UK
| | - Mirjam van der Burg
- Department of Immunology, Erasmus University Medical Center, Rotterdam 3000 CA, Netherlands
| | - Karin R Engelhardt
- Translational and Clinical Research Institute, Newcastle University, NE2 4HH Newcastle upon Tyne, UK
| | - Asbjørg Stray-Pedersen
- Norwegian National Unit for Newborn Screening, Division of Pediatric and Adolescent Medicine, Oslo University Hospital, Oslo 0424, Norway
| | - Hans Christian Erichsen
- Division of Pediatric and Adolescent Medicine, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Oslo 0424, Norway
| | - Andrew R Gennery
- Translational and Clinical Research Institute, Newcastle University, NE2 4HH Newcastle upon Tyne, UK
- Great North Children's Hospital, Newcastle upon Tyne Hospitals NHS Foundation Trust, NE1 4LP Newcastle upon Tyne, UK
| | - Matthias Trost
- Biosciences Institute, Newcastle University, NE2 4HH Newcastle upon Tyne, UK
| | - David J Adams
- Wellcome Sanger Institute, Wellcome Genome Campus, CB10 1SA Hinxton, UK
| | - Graham Anderson
- Institute of Immunology and Immunotherapy, University of Birmingham. B15 2TT Birmingham, UK
| | - Anna Lorenc
- Wellcome Sanger Institute, Wellcome Genome Campus, CB10 1SA Hinxton, UK
| | - Gosia Trynka
- Wellcome Sanger Institute, Wellcome Genome Campus, CB10 1SA Hinxton, UK
- Open Targets, Wellcome Genome Campus, CB10 1SA Hinxton, UK
| | - Sophie Hambleton
- Translational and Clinical Research Institute, Newcastle University, NE2 4HH Newcastle upon Tyne, UK
- Great North Children's Hospital, Newcastle upon Tyne Hospitals NHS Foundation Trust, NE1 4LP Newcastle upon Tyne, UK
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23
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Stoneman HR, Price A, Trout NS, Lamont R, Tifour S, Pozdeyev N, Crooks K, Lin M, Rafaels N, Gignoux CR, Marker KM, Hendricks AE. Characterizing substructure via mixture modeling in large-scale genetic summary statistics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.29.577805. [PMID: 38766180 PMCID: PMC11100604 DOI: 10.1101/2024.01.29.577805] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Genetic summary data are broadly accessible and highly useful including for risk prediction, causal inference, fine mapping, and incorporation of external controls. However, collapsing individual-level data into groups masks intra- and inter-sample heterogeneity, leading to confounding, reduced power, and bias. Ultimately, unaccounted substructure limits summary data usability, especially for understudied or admixed populations. Here, we present Summix2, a comprehensive set of methods and software based on a computationally efficient mixture model to estimate and adjust for substructure in genetic summary data. In extensive simulations and application to public data, Summix2 characterizes finer-scale population structure, identifies ascertainment bias, and identifies potential regions of selection due to local substructure deviation. Summix2 increases the robust use of diverse publicly available summary data resulting in improved and more equitable research.
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Affiliation(s)
- Hayley R Stoneman
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Human Medical Genetics and Genomics Program, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Adelle Price
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA
| | - Nikole Scribner Trout
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA
| | - Riley Lamont
- Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA
| | - Souha Tifour
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA
| | - Nikita Pozdeyev
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Kristy Crooks
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Department of Pathology, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Meng Lin
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Nicholas Rafaels
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Christopher R Gignoux
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Human Medical Genetics and Genomics Program, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Katie M Marker
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Human Medical Genetics and Genomics Program, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Audrey E Hendricks
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Human Medical Genetics and Genomics Program, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
- Mathematical and Statistical Sciences, University of Colorado Denver, Denver, CO 80204, USA
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24
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Liu X, Koyama S, Tomizuka K, Takata S, Ishikawa Y, Ito S, Kosugi S, Suzuki K, Hikino K, Koido M, Koike Y, Horikoshi M, Gakuhari T, Ikegawa S, Matsuda K, Momozawa Y, Ito K, Kamatani Y, Terao C. Decoding triancestral origins, archaic introgression, and natural selection in the Japanese population by whole-genome sequencing. SCIENCE ADVANCES 2024; 10:eadi8419. [PMID: 38630824 PMCID: PMC11023554 DOI: 10.1126/sciadv.adi8419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Accepted: 03/07/2024] [Indexed: 04/19/2024]
Abstract
We generated Japanese Encyclopedia of Whole-Genome/Exome Sequencing Library (JEWEL), a high-depth whole-genome sequencing dataset comprising 3256 individuals from across Japan. Analysis of JEWEL revealed genetic characteristics of the Japanese population that were not discernible using microarray data. First, rare variant-based analysis revealed an unprecedented fine-scale genetic structure. Together with population genetics analysis, the present-day Japanese can be decomposed into three ancestral components. Second, we identified unreported loss-of-function (LoF) variants and observed that for specific genes, LoF variants appeared to be restricted to a more limited set of transcripts than would be expected by chance, with PTPRD as a notable example. Third, we identified 44 archaic segments linked to complex traits, including a Denisovan-derived segment at NKX6-1 associated with type 2 diabetes. Most of these segments are specific to East Asians. Fourth, we identified candidate genetic loci under recent natural selection. Overall, our work provided insights into genetic characteristics of the Japanese population.
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Affiliation(s)
- Xiaoxi Liu
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
| | - Satoshi Koyama
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Kohei Tomizuka
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Sadaaki Takata
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yuki Ishikawa
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Shuji Ito
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory for Bone and Joint Diseases, RIKEN Center for Medical Sciences, Tokyo, Japan
- Department of Orthopedic Surgery, Faculty of Medicine, Shimane University, Izumo, Japan
| | - Shunichi Kosugi
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Kunihiko Suzuki
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Keiko Hikino
- Laboratory for Pharmacogenomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Masaru Koido
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yoshinao Koike
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory for Bone and Joint Diseases, RIKEN Center for Medical Sciences, Tokyo, Japan
- Department of Orthopedic Surgery, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Momoko Horikoshi
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Takashi Gakuhari
- Institute for the Study of Ancient Civilizations and Cultural Resources, College of Human and Social Sciences, Kanazawa University, Kanazawa, Japan
| | - Shiro Ikegawa
- Laboratory for Bone and Joint Diseases, RIKEN Center for Medical Sciences, Tokyo, Japan
| | - Kochi 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
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Kaoru Ito
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
- The Department of Applied Genetics, The School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
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25
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Durward-Akhurst SA, Marlowe JL, Schaefer RJ, Springer K, Grantham B, Carey WK, Bellone RR, Mickelson JR, McCue ME. Predicted genetic burden and frequency of phenotype-associated variants in the horse. Sci Rep 2024; 14:8396. [PMID: 38600096 PMCID: PMC11006912 DOI: 10.1038/s41598-024-57872-8] [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: 12/20/2023] [Accepted: 03/22/2024] [Indexed: 04/12/2024] Open
Abstract
Disease-causing variants have been identified for less than 20% of suspected equine genetic diseases. Whole genome sequencing (WGS) allows rapid identification of rare disease causal variants. However, interpreting the clinical variant consequence is confounded by the number of predicted deleterious variants that healthy individuals carry (predicted genetic burden). Estimation of the predicted genetic burden and baseline frequencies of known deleterious or phenotype associated variants within and across the major horse breeds have not been performed. We used WGS of 605 horses across 48 breeds to identify 32,818,945 variants, demonstrate a high predicted genetic burden (median 730 variants/horse, interquartile range: 613-829), show breed differences in predicted genetic burden across 12 target breeds, and estimate the high frequencies of some previously reported disease variants. This large-scale variant catalog for a major and highly athletic domestic animal species will enhance its ability to serve as a model for human phenotypes and improves our ability to discover the bases for important equine phenotypes.
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Affiliation(s)
- S A Durward-Akhurst
- Department of Veterinary Clinical Sciences, University of Minnesota, C339 VMC, 1353 Boyd Avenue, St. Paul, MN, 55108, USA.
| | - J L Marlowe
- Department of Veterinary Clinical Sciences, University of Minnesota, C339 VMC, 1353 Boyd Avenue, St. Paul, MN, 55108, USA
| | - R J Schaefer
- Department of Veterinary Population Medicine, University of Minnesota, 225 VMC, 1365 Gortner Avenue, St. Paul, MN, 55108, USA
| | - K Springer
- Department of Veterinary Population Medicine, University of Minnesota, 225 VMC, 1365 Gortner Avenue, St. Paul, MN, 55108, USA
| | - B Grantham
- Interval Bio LLC, 408 Stierline Road, Mountain View, CA, 94043, USA
| | - W K Carey
- Interval Bio LLC, 408 Stierline Road, Mountain View, CA, 94043, USA
| | - R R Bellone
- Veterinary Genetics Laboratory, School of Veterinary Medicine, University of California-Davis, Davis, CA, USA
- Population Health and Reproduction and Veterinary Genetics Laboratory, School of Veterinary Medicine, University of California, Davis, CA, USA
| | - J R Mickelson
- Department of Veterinary and Biomedical Sciences, University of Minnesota, 295F Animal Science Veterinary Medicine Building, 1988 Fitch Avenue, St. Paul, MN, 55108, USA
| | - M E McCue
- Department of Veterinary Population Medicine, University of Minnesota, 225 VMC, 1365 Gortner Avenue, St. Paul, MN, 55108, USA
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26
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Basu A, Dutta AK, Bagepally BS, Das S, Cherian JJ, Roy S, Maurya PK, Saha I, Sukumaran D, Rina K, Mandal S, Sarkar S, Kalita M, Bhowmik K, Saha A, Chakrabarti A. Pharmacogenomics-assisted schizophrenia management: A hybrid type 2 effectiveness-implementation study protocol to compare the clinical utility, cost-effectiveness, and barriers. PLoS One 2024; 19:e0300511. [PMID: 38598465 PMCID: PMC11006179 DOI: 10.1371/journal.pone.0300511] [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: 10/03/2023] [Accepted: 02/28/2024] [Indexed: 04/12/2024] Open
Abstract
OBJECTIVES The response to antipsychotic therapy is highly variable. Pharmacogenomic (PGx) factors play a major role in deciding the effectiveness and safety of antipsychotic drugs. A hybrid type 2 effectiveness-implementation research will be conducted to evaluate the clinical utility (safety and efficacy), cost-effectiveness, and facilitators and barriers in implementing PGx-assisted management compared to standard of care in patients with schizophrenia attending a tertiary care hospital in eastern India. METHODS In part 1, a randomized controlled trial will be conducted. Adult patients with schizophrenia will be randomized (2: 1) to receive PGx-assisted treatment (drug and regimen selection depending on the results of single-nucleotide polymorphisms in genes DRD2, HTR1A, HTR2C, ABCB1, CYP2D6, CYP3A5, and CYP1A2) or the standard of care. Serum drug levels will be measured. The patients will be followed up for 12 weeks. The primary endpoint is the difference in the Udvalg for Kliniske Undersøgelser Side-Effect Rating Scale score between the two arms. In part 2, the cost-effectiveness of PGx-assisted treatment will be evaluated. In part 3, the facilitators and barriers to implementing PGx-assisted treatment for schizophrenia will be explored using a qualitative design. EXPECTED OUTCOME The study findings will help in understanding whether PGx-assisted management has a clinical utility, whether it is cost-effective, and what are the facilitators and barriers to implementing it in the management of schizophrenia. TRIAL REGISTRATION The study has been registered with the Clinical Trials Registry-India (CTRI/2023/08/056210).
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Affiliation(s)
- Aniruddha Basu
- Department of Psychiatry, All India Institute of Medical Sciences, Kalyani, India
| | - Atanu Kumar Dutta
- Department of Biochemistry, All India Institute of Medical Sciences, Kalyani, India
| | | | - Saibal Das
- Indian Council of Medical Research, Centre for Ageing and Mental Health, Kolkata, India
- Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden
| | - Jerin Jose Cherian
- Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden
- Indian Council of Medical Research, New Delhi, India
| | - Sudipto Roy
- Indian Council of Medical Research, New Delhi, India
| | - Pawan Kumar Maurya
- Indian Council of Medical Research, Centre for Ageing and Mental Health, Kolkata, India
| | - Indranil Saha
- Indian Council of Medical Research, Centre for Ageing and Mental Health, Kolkata, India
| | - Deepasree Sukumaran
- Department of Pharmacology, All India Institute of Medical Sciences, Kalyani, India
| | - Kumari Rina
- Department of Psychiatry, All India Institute of Medical Sciences, Kalyani, India
| | - Sucharita Mandal
- Department of Psychiatry, All India Institute of Medical Sciences, Kalyani, India
| | - Sukanto Sarkar
- Department of Psychiatry, All India Institute of Medical Sciences, Kalyani, India
| | - Manoj Kalita
- Indian Council of Medical Research, Centre for Ageing and Mental Health, Kolkata, India
| | - Kalyan Bhowmik
- Indian Council of Medical Research, Centre for Ageing and Mental Health, Kolkata, India
| | - Asim Saha
- Indian Council of Medical Research, Centre for Ageing and Mental Health, Kolkata, India
| | - Amit Chakrabarti
- Indian Council of Medical Research, Centre for Ageing and Mental Health, Kolkata, India
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27
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Aamer W, Al-Maraghi A, Syed N, Gandhi GD, Aliyev E, Al-Kurbi AA, Al-Saei O, Kohailan M, Krishnamoorthy N, Palaniswamy S, Al-Malki K, Abbasi S, Agrebi N, Abbaszadeh F, Akil ASAS, Badii R, Ben-Omran T, Lo B, Mokrab Y, Fakhro KA. Burden of Mendelian disorders in a large Middle Eastern biobank. Genome Med 2024; 16:46. [PMID: 38584274 PMCID: PMC11000384 DOI: 10.1186/s13073-024-01307-6] [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: 07/01/2023] [Accepted: 02/19/2024] [Indexed: 04/09/2024] Open
Abstract
BACKGROUND Genome sequencing of large biobanks from under-represented ancestries provides a valuable resource for the interrogation of Mendelian disease burden at world population level, complementing small-scale familial studies. METHODS Here, we interrogate 6045 whole genomes from Qatar-a Middle Eastern population with high consanguinity and understudied mutational burden-enrolled at the national Biobank and phenotyped for 58 clinically-relevant quantitative traits. We examine a curated set of 2648 Mendelian genes from 20 panels, annotating known and novel pathogenic variants and assessing their penetrance and impact on the measured traits. RESULTS We find that 62.5% of participants are carriers of at least 1 known pathogenic variant relating to recessive conditions, with homozygosity observed in 1 in 150 subjects (0.6%) for which Peninsular Arabs are particularly enriched versus other ancestries (5.8-fold). On average, 52.3 loss-of-function variants were found per genome, 6.5 of which affect a known Mendelian gene. Several variants annotated in ClinVar/HGMD as pathogenic appeared at intermediate frequencies in this cohort (1-3%), highlighting Arab founder effect, while others have exceedingly high frequencies (> 5%) prompting reconsideration as benign. Furthermore, cumulative gene burden analysis revealed 56 genes having gene carrier frequency > 1/50, including 5 ACMG Tier 3 panel genes which would be candidates for adding to newborn screening in the country. Additionally, leveraging 58 biobank traits, we systematically assess the impact of novel/rare variants on phenotypes and discover 39 candidate large-effect variants associating with extreme quantitative traits. Furthermore, through rare variant burden testing, we discover 13 genes with high mutational load, including 5 with impact on traits relevant to disease conditions, including metabolic disorder and type 2 diabetes, consistent with the high prevalence of these conditions in the region. CONCLUSIONS This study on the first phase of the growing Qatar Genome Program cohort provides a comprehensive resource from a Middle Eastern population to understand the global mutational burden in Mendelian genes and their impact on traits in seemingly healthy individuals in high consanguinity settings.
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Affiliation(s)
- Waleed Aamer
- Department of Human Genetics, Sidra Medicine, Doha, Qatar
| | | | - Najeeb Syed
- Applied Bioinformatics Core, Sidra Medicine, Doha, Qatar
| | | | - Elbay Aliyev
- Department of Human Genetics, Sidra Medicine, Doha, Qatar
| | | | - Omayma Al-Saei
- Department of Human Genetics, Sidra Medicine, Doha, Qatar
| | | | | | | | | | - Saleha Abbasi
- Department of Human Genetics, Sidra Medicine, Doha, Qatar
| | - Nourhen Agrebi
- Department of Human Genetics, Sidra Medicine, Doha, Qatar
| | | | | | - Ramin Badii
- Diagnostic Genomic Division, Hamad Medical Corporation, Doha, Qatar
| | - Tawfeg Ben-Omran
- Section of Clinical and Metabolic Genetics, Department of pediatrics, Hamad Medical Corporation, Doha, Qatar
- Department of Pediatric, Weill Cornell Medical College, Doha, Qatar
- Division of Genetic & Genomics Medicine, Sidra Medicine, Doha, Qatar
| | - Bernice Lo
- Department of Human Genetics, Sidra Medicine, Doha, Qatar
- College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar
| | - Younes Mokrab
- Department of Human Genetics, Sidra Medicine, Doha, Qatar.
- Department of Genetic Medicine, Weill Cornell Medicine-Qatar, Doha, Qatar.
- College of Health Sciences, Qatar University, Doha, Qatar.
| | - Khalid A Fakhro
- Department of Human Genetics, Sidra Medicine, Doha, Qatar.
- College of Health and Life Sciences, Hamad Bin Khalifa University, Doha, Qatar.
- Department of Genetic Medicine, Weill Cornell Medicine-Qatar, Doha, Qatar.
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28
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Islam A, Manjarrez-González JC, Song X, Gore T, Draviam VM. Search for chromosomal instability aiding variants reveal naturally occurring kinetochore gene variants that perturb chromosome segregation. iScience 2024; 27:109007. [PMID: 38361632 PMCID: PMC10867425 DOI: 10.1016/j.isci.2024.109007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 10/15/2023] [Accepted: 01/19/2024] [Indexed: 02/17/2024] Open
Abstract
Chromosomal instability (CIN) is a hallmark of cancers, and CIN-promoting mutations are not fully understood. Here, we report 141 chromosomal instability aiding variant (CIVa) candidates by assessing the prevalence of loss-of-function (LoF) variants in 135 chromosome segregation genes from over 150,000 humans. Unexpectedly, we observe both heterozygous and homozygous CIVa in Astrin and SKA3, two evolutionarily conserved kinetochore and microtubule-associated proteins essential for chromosome segregation. To stratify harmful versus harmless variants, we combine live-cell microscopy and controlled protein expression. We find the naturally occurring Astrin p.Q1012∗ variant is harmful as it fails to localize normally and induces chromosome misalignment and missegregation, in a dominant negative manner. In contrast, the Astrin p.L7Qfs∗21 variant generates a shorter isoform that localizes and functions normally, and the SKA3 p.Q70Kfs∗7 variant allows wild-type SKA complex localisation and function, revealing distinct resilience mechanisms that render these variants harmless. Thus, we present a scalable framework to predict and stratify naturally occurring CIVa, and provide insight into resilience mechanisms that compensate for naturally occurring CIVa.
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Affiliation(s)
- Asifa Islam
- School of Biological and Chemical Sciences, Queen Mary, University of London, London E1 4NS, UK
| | | | - Xinhong Song
- School of Biological and Chemical Sciences, Queen Mary, University of London, London E1 4NS, UK
| | - Trupti Gore
- School of Biological and Chemical Sciences, Queen Mary, University of London, London E1 4NS, UK
- London Interdisciplinary Doctoral Program, University College London, London, UK
| | - Viji M. Draviam
- School of Biological and Chemical Sciences, Queen Mary, University of London, London E1 4NS, UK
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Bastaki K, Velayutham D, Irfan A, Adnan M, Mohammed S, Mbarek H, Qoronfleh MW, Jithesh PV. Forging the path to precision medicine in Qatar: a public health perspective on pharmacogenomics initiatives. Front Public Health 2024; 12:1364221. [PMID: 38550311 PMCID: PMC10977610 DOI: 10.3389/fpubh.2024.1364221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2024] [Accepted: 02/20/2024] [Indexed: 04/02/2024] Open
Abstract
Pharmacogenomics (PGx) is an important component of precision medicine that promises tailored treatment approaches based on an individual's genetic information. Exploring the initiatives in research that help to integrate PGx test into clinical setting, identifying the potential barriers and challenges as well as planning the future directions, are all important for fruitful PGx implementation in any population. Qatar serves as an exemplar case study for the Middle East, having a small native population compared to a diverse immigrant population, advanced healthcare system, national genome program, and several educational initiatives on PGx and precision medicine. This paper attempts to outline the current state of PGx research and implementation in Qatar within the global context, emphasizing ongoing initiatives and educational efforts. The inclusion of PGx in university curricula and healthcare provider training, alongside precision medicine conferences, showcase Qatar's commitment to advancing this field. However, challenges persist, including the requirement for population specific implementation strategies, complex genetic data interpretation, lack of standardization, and limited awareness. The review suggests policy development for future directions in continued research investment, conducting clinical trials for the feasibility of PGx implementation, ethical considerations, technological advancements, and global collaborations to overcome these barriers.
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Affiliation(s)
- Kholoud Bastaki
- Clinical and Pharmacy Practice Department, College of Pharmacy, QU Health, Qatar University, Doha, Qatar
| | - Dinesh Velayutham
- College of Health & Life Sciences, Hamad Bin Khalifa University, Education City, Doha, Qatar
| | - Areeba Irfan
- College of Health & Life Sciences, Hamad Bin Khalifa University, Education City, Doha, Qatar
| | - Mohd Adnan
- College of Health & Life Sciences, Hamad Bin Khalifa University, Education City, Doha, Qatar
| | - Sawsan Mohammed
- College of Medicine, Pre-Clinical Education Department, QU Health, Qatar University, Doha, Qatar
| | | | - M. Waild Qoronfleh
- Q3 Research Institute (QRI), Research & Policy Division, Ann Arbor, MI, United States
| | - Puthen Veettil Jithesh
- College of Health & Life Sciences, Hamad Bin Khalifa University, Education City, Doha, Qatar
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Nzitakera A, Surwumwe JB, Ndoricyimpaye EL, Uwamungu S, Uwamariya D, Manirakiza F, Ndayisaba MC, Ntakirutimana G, Seminega B, Dusabejambo V, Rutaganda E, Kamali P, Ngabonziza F, Ishikawa R, Rugwizangoga B, Iwashita Y, Yamada H, Yoshimura K, Sugimura H, Shinmura K. The spectrum of TP53 mutations in Rwandan patients with gastric cancer. Genes Environ 2024; 46:8. [PMID: 38459566 PMCID: PMC10921722 DOI: 10.1186/s41021-024-00302-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Accepted: 02/18/2024] [Indexed: 03/10/2024] Open
Abstract
BACKGROUND Gastric cancer is the sixth most frequently diagnosed cancer and third in causing cancer-related death globally. The most frequently mutated gene in human cancers is TP53, which plays a pivotal role in cancer initiation and progression. In Africa, particularly in Rwanda, data on TP53 mutations are lacking. Therefore, this study intended to obtain TP53 mutation status in Rwandan patients with gastric cancer. RESULTS Formalin-fixed paraffin-embedded tissue blocks of 95 Rwandan patients with histopathologically proven gastric carcinoma were obtained from the University Teaching Hospital of Kigali. After DNA extraction, all coding regions of the TP53 gene and the exon-intron boundary region of TP53 were sequenced using the Sanger sequencing. Mutated TP53 were observed in 24 (25.3%) of the 95 cases, and a total of 29 mutations were identified. These TP53 mutations were distributed between exon 4 and 8 and most of them were missense mutations (19/29; 65.5%). Immunohistochemical analysis for TP53 revealed that most of the TP53 missense mutations were associated with TP53 protein accumulation. Among the 29 mutations, one was novel (c.459_477delCGGCACCCGCGTCCGCGCC). This 19-bp deletion mutation in exon 5 caused the production of truncated TP53 protein (p.G154Wfs*10). Regarding the spectrum of TP53 mutations, G:C > A:T at CpG sites was the most prevalent (10/29; 34.5%) and G:C > T:A was the second most prevalent (7/29; 24.1%). Interestingly, when the mutation spectrum of TP53 was compared to three previous TP53 mutational studies on non-Rwandan patients with gastric cancer, G:C > T:A mutations were significantly more frequent in this study than in our previous study (p = 0.013), the TCGA database (p = 0.017), and a previous study on patients from Hong Kong (p = 0.006). Even after correcting for false discovery, statistical significance was observed. CONCLUSIONS Our results suggested that TP53 G:C > T:A transversion mutation in Rwandan patients with gastric cancer is more frequent than in non-Rwandan patients with gastric cancer, indicating at an alternative etiological and carcinogenic progression of gastric cancer in Rwanda.
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Affiliation(s)
- Augustin Nzitakera
- Department of Tumor Pathology, Hamamatsu University School of Medicine (HUSM), 1-20-1 Handayama, Higashi-Ku, Hamamatsu, Shizuoka, 431-3192, Japan
- Department of Biomedical Laboratory Sciences, School of Health Sciences, College of Medicine and Health Sciences, University of Rwanda, P.O. Box 3286, Kigali, Rwanda
| | - Jean Bosco Surwumwe
- Department of Pathology, University Teaching Hospital of Kigali, P.O. Box 655, Kigali, Rwanda
| | - Ella Larissa Ndoricyimpaye
- Department of Biomedical Laboratory Sciences, School of Health Sciences, College of Medicine and Health Sciences, University of Rwanda, P.O. Box 3286, Kigali, Rwanda
- Université Catholique de Louvain, Médecine Expérimentale, Brussels, 1348, Belgium
| | - Schifra Uwamungu
- Department of Biomedical Laboratory Sciences, School of Health Sciences, College of Medicine and Health Sciences, University of Rwanda, P.O. Box 3286, Kigali, Rwanda
- Department of Pharmacology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, SE-40530, Sweden
| | - Delphine Uwamariya
- Department of Biomedical Laboratory Sciences, School of Health Sciences, College of Medicine and Health Sciences, University of Rwanda, P.O. Box 3286, Kigali, Rwanda
- Department of Pathology, University Teaching Hospital of Kigali, P.O. Box 655, Kigali, Rwanda
- Department of Pathology, School of Medicine and Pharmacy, College of Medicine and Health Sciences, University of Rwanda, P.O. Box 3286, Kigali, Rwanda
| | - Felix Manirakiza
- Department of Tumor Pathology, Hamamatsu University School of Medicine (HUSM), 1-20-1 Handayama, Higashi-Ku, Hamamatsu, Shizuoka, 431-3192, Japan
- Department of Pathology, University Teaching Hospital of Kigali, P.O. Box 655, Kigali, Rwanda
- Department of Pathology, School of Medicine and Pharmacy, College of Medicine and Health Sciences, University of Rwanda, P.O. Box 3286, Kigali, Rwanda
| | - Marie Claire Ndayisaba
- Department of Pathology, University Teaching Hospital of Kigali, P.O. Box 655, Kigali, Rwanda
- Department of Pathology, School of Medicine and Pharmacy, College of Medicine and Health Sciences, University of Rwanda, P.O. Box 3286, Kigali, Rwanda
| | - Gervais Ntakirutimana
- Department of Pathology, University Teaching Hospital of Kigali, P.O. Box 655, Kigali, Rwanda
- Department of Pathology, School of Medicine and Pharmacy, College of Medicine and Health Sciences, University of Rwanda, P.O. Box 3286, Kigali, Rwanda
| | - Benoit Seminega
- Department of Pathology, School of Medicine and Pharmacy, College of Medicine and Health Sciences, University of Rwanda, P.O. Box 3286, Kigali, Rwanda
- Department of Internal Medicine, University Teaching Hospital of Kigali, P.O. Box 655, Kigali, Rwanda
| | - Vincent Dusabejambo
- Department of Pathology, School of Medicine and Pharmacy, College of Medicine and Health Sciences, University of Rwanda, P.O. Box 3286, Kigali, Rwanda
- Department of Internal Medicine, University Teaching Hospital of Kigali, P.O. Box 655, Kigali, Rwanda
| | - Eric Rutaganda
- Department of Pathology, School of Medicine and Pharmacy, College of Medicine and Health Sciences, University of Rwanda, P.O. Box 3286, Kigali, Rwanda
- Department of Internal Medicine, University Teaching Hospital of Kigali, P.O. Box 655, Kigali, Rwanda
| | - Placide Kamali
- Department of Pathology, School of Medicine and Pharmacy, College of Medicine and Health Sciences, University of Rwanda, P.O. Box 3286, Kigali, Rwanda
- Department of Internal Medicine, University Teaching Hospital of Kigali, P.O. Box 655, Kigali, Rwanda
| | - François Ngabonziza
- Department of Pathology, School of Medicine and Pharmacy, College of Medicine and Health Sciences, University of Rwanda, P.O. Box 3286, Kigali, Rwanda
- Department of Internal Medicine, University Teaching Hospital of Kigali, P.O. Box 655, Kigali, Rwanda
| | - Rei Ishikawa
- Department of Tumor Pathology, Hamamatsu University School of Medicine (HUSM), 1-20-1 Handayama, Higashi-Ku, Hamamatsu, Shizuoka, 431-3192, Japan
| | - Belson Rugwizangoga
- Department of Pathology, University Teaching Hospital of Kigali, P.O. Box 655, Kigali, Rwanda
- Department of Pathology, School of Medicine and Pharmacy, College of Medicine and Health Sciences, University of Rwanda, P.O. Box 3286, Kigali, Rwanda
| | - Yuji Iwashita
- Department of Tumor Pathology, Hamamatsu University School of Medicine (HUSM), 1-20-1 Handayama, Higashi-Ku, Hamamatsu, Shizuoka, 431-3192, Japan
| | - Hidetaka Yamada
- Department of Tumor Pathology, Hamamatsu University School of Medicine (HUSM), 1-20-1 Handayama, Higashi-Ku, Hamamatsu, Shizuoka, 431-3192, Japan
| | - Kimio Yoshimura
- Department of Health Policy and Management, Keio University School of Medicine, Tokyo, 160-8582, Japan
| | - Haruhiko Sugimura
- Department of Tumor Pathology, Hamamatsu University School of Medicine (HUSM), 1-20-1 Handayama, Higashi-Ku, Hamamatsu, Shizuoka, 431-3192, Japan.
- Sasaki Institute Sasaki Foundation, 2-2 Kanda Surugadai, Chiyoda-Ku, Tokyo, 101-0062, Japan.
| | - Kazuya Shinmura
- Department of Tumor Pathology, Hamamatsu University School of Medicine (HUSM), 1-20-1 Handayama, Higashi-Ku, Hamamatsu, Shizuoka, 431-3192, Japan.
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Kerdoncuff E, Skov L, Patterson N, Zhao W, Lueng YY, Schellenberg GD, Smith JA, Dey S, Ganna A, Dey AB, Kardia SL, Lee J, Moorjani P. 50,000 years of Evolutionary History of India: Insights from ~2,700 Whole Genome Sequences. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.15.580575. [PMID: 38405782 PMCID: PMC10888882 DOI: 10.1101/2024.02.15.580575] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
India has been underrepresented in whole genome sequencing studies. We generated 2,762 high coverage genomes from India-including individuals from most geographic regions, speakers of all major languages, and tribal and caste groups-providing a comprehensive survey of genetic variation in India. With these data, we reconstruct the evolutionary history of India through space and time at fine scales. We show that most Indians derive ancestry from three ancestral groups related to ancient Iranian farmers, Eurasian Steppe pastoralists and South Asian hunter-gatherers. We uncover a common source of Iranian-related ancestry from early Neolithic cultures of Central Asia into the ancestors of Ancestral South Indians (ASI), Ancestral North Indians (ANI), Austro-asiatic-related and East Asian-related groups in India. Following these admixtures, India experienced a major demographic shift towards endogamy, resulting in extensive homozygosity and identity-by-descent sharing among individuals. At deep time scales, Indians derive around 1-2% of their ancestry from gene flow from archaic hominins, Neanderthals and Denisovans. By assembling the surviving fragments of archaic ancestry in modern Indians, we recover ~1.5 Gb (or 50%) of the introgressing Neanderthal and ~0.6 Gb (or 20%) of the introgressing Denisovan genomes, more than any other previous archaic ancestry study. Moreover, Indians have the largest variation in Neanderthal ancestry, as well as the highest amount of population-specific Neanderthal segments among worldwide groups. Finally, we demonstrate that most of the genetic variation in Indians stems from a single major migration out of Africa that occurred around 50,000 years ago, with minimal contribution from earlier migration waves. Together, these analyses provide a detailed view of the population history of India and underscore the value of expanding genomic surveys to diverse groups outside Europe.
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Affiliation(s)
- Elise Kerdoncuff
- Department of Molecular and Cell Biology, University of California, Berkeley, United States of America
| | - Laurits Skov
- Department of Molecular and Cell Biology, University of California, Berkeley, United States of America
| | - Nick Patterson
- Department of Human Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America
| | - Wei Zhao
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, United States of America
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Yuk Yee Lueng
- Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, United States of America
| | - Gerard D. Schellenberg
- Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, United States of America
| | - Jennifer A. Smith
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, United States of America
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Sharmistha Dey
- Department of Biophysics, All India Institute of Medical Sciences, New Delhi, India
| | - Andrea Ganna
- Institute for Molecular Medicine Finland, Helsinki, Finland
| | - AB Dey
- Department of Geriatric Medicine, All India Institute of Medical Sciences, New Delhi, India
| | - Sharon L.R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Jinkook Lee
- Department of Economics, and Center for Economic & Social Research, University of Southern California, Los Angeles, California, United States of America
| | - Priya Moorjani
- Department of Molecular and Cell Biology, University of California, Berkeley, United States of America
- Center for Computational Biology, University of California, Berkeley, United States of America
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32
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Andrews SV, Kukkle PL, Menon R, Geetha TS, Goyal V, Kandadai RM, Kumar H, Borgohain R, Mukherjee A, Wadia PM, Yadav R, Desai S, Kumar N, Joshi D, Murugan S, Biswas A, Pal PK, Oliver M, Nair S, Kayalvizhi A, Samson PL, Deshmukh M, Bassi A, Sandeep C, Mandloi N, Davis OB, Roberts MA, Leto DE, Henry AG, Di Paolo G, Muthane U, Das SK, Peterson AS, Sandmann T, Gupta R, Ramprasad VL. The Genetic Drivers of Juvenile, Young, and Early-Onset Parkinson's Disease in India. Mov Disord 2024; 39:339-349. [PMID: 38014556 DOI: 10.1002/mds.29676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 10/18/2023] [Accepted: 11/09/2023] [Indexed: 11/29/2023] Open
Abstract
BACKGROUND Recent studies have advanced our understanding of the genetic drivers of Parkinson's disease (PD). Rare variants in more than 20 genes are considered causal for PD, and the latest PD genome-wide association study (GWAS) identified 90 independent risk loci. However, there remains a gap in our understanding of PD genetics outside of the European populations in which the vast majority of these studies were focused. OBJECTIVE The aim was to identify genetic risk factors for PD in a South Asian population. METHODS A total of 674 PD subjects predominantly with age of onset (AoO) ≤50 years (encompassing juvenile, young, or early-onset PD) were recruited from 10 specialty movement disorder centers across India over a 2-year period; 1376 control subjects were selected from the reference population GenomeAsia, Phase 2. We performed various case-only and case-control genetic analyses for PD diagnosis and AoO. RESULTS A genome-wide significant signal for PD diagnosis was identified in the SNCA region, strongly colocalizing with SNCA region signal from European PD GWAS. PD cases with pathogenic mutations in PD genes exhibited, on average, lower PD polygenic risk scores than PD cases lacking any PD gene mutations. Gene burden studies of rare, predicted deleterious variants identified BSN, encoding the presynaptic protein Bassoon that has been previously associated with neurodegenerative disease. CONCLUSIONS This study constitutes the largest genetic investigation of PD in a South Asian population to date. Future work should seek to expand sample numbers in this population to enable improved statistical power to detect PD genes in this understudied group. © 2023 Denali Therapeutics and The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Shan V Andrews
- Denali Therapeutics, South San Francisco, California, USA
| | - Prashanth L Kukkle
- Manipal Hospital, Bangalore, India
- Parkinson's Disease and Movement Disorders Clinic, Bangalore, India
| | | | | | - Vinay Goyal
- All India Institute of Medical Sciences (AIIMS), New Delhi, India
- Medanta Hospital, New Delhi, India
- Medanta, The Medicity, Gurgaon, India
| | - Rukmini Mridula Kandadai
- Nizams Institute of Medical Sciences (NIMS), Hyderabad, India
- Citi Neuro Centre, Hyderabad, India
| | | | - Rupam Borgohain
- Nizams Institute of Medical Sciences (NIMS), Hyderabad, India
- Citi Neuro Centre, Hyderabad, India
| | - Adreesh Mukherjee
- Bangur Institute of Neurosciences and Institute of Post Graduate Medical Education and Research (IPGME&R), Kolkata, India
| | | | - Ravi Yadav
- National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, India
| | - Soaham Desai
- Department of Neurology, Shree Krishna Hospital and Pramukhaswami Medical College, Bhaikaka University, Anand, India
| | - Niraj Kumar
- All India Institute of Medical Sciences, Rishikesh, India
- All India Institute of Medical Sciences, Bibinagar (Hyderabad Metropolitan Region), Bibinagar, India
| | - Deepika Joshi
- Department of Neurology, Institute of Medical Sciences, Banaras Hindu University, Varanasi, India
| | | | - Atanu Biswas
- Bangur Institute of Neurosciences and Institute of Post Graduate Medical Education and Research (IPGME&R), Kolkata, India
| | - Pramod K Pal
- National Institute of Mental Health and Neurosciences (NIMHANS), Bangalore, India
| | | | | | | | | | | | | | | | | | - Oliver B Davis
- Denali Therapeutics, South San Francisco, California, USA
| | | | - Dara E Leto
- Denali Therapeutics, South San Francisco, California, USA
| | | | | | - Uday Muthane
- Parkinson and Ageing Research Foundation, Bangalore, India
| | - Shymal K Das
- Bangur Institute of Neurosciences and Institute of Post Graduate Medical Education and Research (IPGME&R), Kolkata, India
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Huang S, Liu S, Huang M, He JR, Wang C, Wang T, Feng X, Kuang Y, Lu J, Gu Y, Xia X, Lin S, Zhou W, Fu Q, Xia H, Qiu X. The Born in Guangzhou Cohort Study enables generational genetic discoveries. Nature 2024; 626:565-573. [PMID: 38297123 DOI: 10.1038/s41586-023-06988-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Accepted: 12/15/2023] [Indexed: 02/02/2024]
Abstract
Genomic research that targets large-scale, prospective birth cohorts constitutes an essential strategy for understanding the influence of genetics and environment on human health1. Nonetheless, such studies remain scarce, particularly in Asia. Here we present the phase I genome study of the Born in Guangzhou Cohort Study2 (BIGCS), which encompasses the sequencing and analysis of 4,053 Chinese individuals, primarily composed of trios or mother-infant duos residing in South China. Our analysis reveals novel genetic variants, a high-quality reference panel, and fine-scale local genetic structure within BIGCS. Notably, we identify previously unreported East Asian-specific genetic associations with maternal total bile acid, gestational weight gain and infant cord blood traits. Additionally, we observe prevalent age-specific genetic effects on lipid levels in mothers and infants. In an exploratory intergenerational Mendelian randomization analysis, we estimate the maternal putatively causal and fetal genetic effects of seven adult phenotypes on seven fetal growth-related measurements. These findings illuminate the genetic links between maternal and early-life traits in an East Asian population and lay the groundwork for future research into the intricate interplay of genetics, intrauterine exposures and early-life experiences in shaping long-term health.
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Affiliation(s)
- Shujia Huang
- Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Siyang Liu
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
| | - Mingxi Huang
- Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Jian-Rong He
- Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
- Provincial Clinical Research Center for Child Health, Guangzhou, China
- Department of Obstetrics and Gynecology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Chengrui Wang
- Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Tianyi Wang
- Key Laboratory of Vertebrate Evolution and Human Origins, Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing, China
- University of the Chinese Academy of Sciences, Beijing, China
| | - Xiaotian Feng
- Key Laboratory of Vertebrate Evolution and Human Origins, Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing, China
- University of the Chinese Academy of Sciences, Beijing, China
| | - Yashu Kuang
- Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
- Provincial Clinical Research Center for Child Health, Guangzhou, China
| | - Jinhua Lu
- Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
- Provincial Clinical Research Center for Child Health, Guangzhou, China
| | - Yuqin Gu
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China
| | - Xiaoyan Xia
- Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
- Department of Women's Health, Provincial Key Clinical Specialty of Woman and Child Health, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Shanshan Lin
- Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
- Department of Women's Health, Provincial Key Clinical Specialty of Woman and Child Health, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Wenhao Zhou
- Division of Neonatology and Center for Newborn Care, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
| | - Qiaomei Fu
- Key Laboratory of Vertebrate Evolution and Human Origins, Institute of Vertebrate Paleontology and Paleoanthropology, Chinese Academy of Sciences, Beijing, China
- University of the Chinese Academy of Sciences, Beijing, China
| | - Huimin Xia
- Provincial Clinical Research Center for Child Health, Guangzhou, China.
- Provincial Key Laboratory of Research in Structure Birth Defect Disease, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China.
- Department of Pediatric Surgery, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China.
| | - Xiu Qiu
- Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China.
- Provincial Clinical Research Center for Child Health, Guangzhou, China.
- Department of Women's Health, Provincial Key Clinical Specialty of Woman and Child Health, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China.
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He G, Wang P, Chen J, Liu Y, Sun Y, Hu R, Duan S, Sun Q, Tang R, Yang J, Wang Z, Yun L, Hu L, Yan J, Nie S, Wei L, Liu C, Wang M. Differentiated genomic footprints suggest isolation and long-distance migration of Hmong-Mien populations. BMC Biol 2024; 22:18. [PMID: 38273256 PMCID: PMC10809681 DOI: 10.1186/s12915-024-01828-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: 01/23/2023] [Accepted: 01/12/2024] [Indexed: 01/27/2024] Open
Abstract
BACKGROUND The underrepresentation of Hmong-Mien (HM) people in Asian genomic studies has hindered our comprehensive understanding of the full landscape of their evolutionary history and complex trait architecture. South China is a multi-ethnic region and indigenously settled by ethnolinguistically diverse HM, Austroasiatic (AA), Tai-Kadai (TK), Austronesian (AN), and Sino-Tibetan (ST) people, which is regarded as East Asia's initial cradle of biodiversity. However, previous fragmented genetic studies have only presented a fraction of the landscape of genetic diversity in this region, especially the lack of haplotype-based genomic resources. The deep characterization of demographic history and natural-selection-relevant genetic architecture of HM people was necessary. RESULTS We reported one HM-specific genomic resource and comprehensively explored the fine-scale genetic structure and adaptative features inferred from the genome-wide SNP data of 440 HM individuals from 33 ethnolinguistic populations, including previously unreported She. We identified solid genetic differentiation between HM people and Han Chinese at 7.64‒15.86 years ago (kya) and split events between southern Chinese inland (Miao/Yao) and coastal (She) HM people in the middle Bronze Age period and the latter obtained more gene flow from Ancient Northern East Asians. Multiple admixture models further confirmed that extensive gene flow from surrounding ST, TK, and AN people entangled in forming the gene pool of Chinese coastal HM people. Genetic findings of isolated shared unique ancestral components based on the sharing alleles and haplotypes deconstructed that HM people from the Yungui Plateau carried the breadth of previously unknown genomic diversity. We identified a direct and recent genetic connection between Chinese inland and Southeast Asian HM people as they shared the most extended identity-by-descent fragments, supporting the long-distance migration hypothesis. Uniparental phylogenetic topology and network-based phylogenetic relationship reconstruction found ancient uniparental founding lineages in southwestern HM people. Finally, the population-specific biological adaptation study identified the shared and differentiated natural selection signatures among inland and coastal HM people associated with physical features and immune functions. The allele frequency spectrum of cancer susceptibility alleles and pharmacogenomic genes showed significant differences between HM and northern Chinese people. CONCLUSIONS Our extensive genetic evidence combined with the historical documents supported the view that ancient HM people originated from the Yungui regions associated with ancient "Three-Miao tribes" descended from the ancient Daxi-Qujialing-Shijiahe people. Then, some have recently migrated rapidly to Southeast Asia, and some have migrated eastward and mixed respectively with Southeast Asian indigenes, Liangzhu-related coastal ancient populations, and incoming southward ST people. Generally, complex population migration, admixture, and adaptation history contributed to the complicated patterns of population structure of geographically diverse HM people.
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Affiliation(s)
- Guanglin He
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China.
- Center for Archaeological Science, Sichuan University, Chengdu, 610000, China.
- Anti-Drug Technology Center of Guangdong Province, Guangzhou, 510230, China.
- Research Center for Genomic Medicine, North Sichuan Medical College, Nanchong, 637100, China.
| | - Peixin Wang
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
- School of Medical Information, Chongqing Medical University, Chongqing, 400331, China
| | - Jing Chen
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, 030001, China
| | - Yan Liu
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
- School of Basic Medical Sciences, North Sichuan Medical College, Nanchong, 637000, China
- Research Center for Genomic Medicine, North Sichuan Medical College, Nanchong, 637100, China
| | - Yuntao Sun
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
- Institute of Forensic Medicine, West China School of Basic Science & Forensic Medicine, Sichuan University, Chengdu, 610041, China
| | - Rong Hu
- School of Sociology and Anthropology, Xiamen University, Xiamen, 361005, China
| | - Shuhan Duan
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
- School of Basic Medical Sciences, North Sichuan Medical College, Nanchong, 637000, China
- Research Center for Genomic Medicine, North Sichuan Medical College, Nanchong, 637100, China
| | - Qiuxia Sun
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
- Department of Forensic Medicine, College of Basic Medicine, Chongqing Medical University, Chongqing, 400331, China
| | - Renkuan Tang
- Department of Forensic Medicine, College of Basic Medicine, Chongqing Medical University, Chongqing, 400331, China
| | - Junbao Yang
- School of Basic Medical Sciences, North Sichuan Medical College, Nanchong, 637000, China
- Research Center for Genomic Medicine, North Sichuan Medical College, Nanchong, 637100, China
| | - Zhiyong Wang
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
- School of Forensic Medicine, Kunming Medical University, Kunming, 650500, China
| | - Libing Yun
- Institute of Forensic Medicine, West China School of Basic Science & Forensic Medicine, Sichuan University, Chengdu, 610041, China
| | - Liping Hu
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China
- School of Forensic Medicine, Kunming Medical University, Kunming, 650500, China
| | - Jiangwei Yan
- School of Forensic Medicine, Shanxi Medical University, Jinzhong, 030001, China
| | - Shengjie Nie
- School of Forensic Medicine, Kunming Medical University, Kunming, 650500, China
| | - Lanhai Wei
- School of Ethnology and Anthropology, Inner Mongolia Normal University, Inner Mongolia, 010028, China
| | - Chao Liu
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510275, China.
- Anti-Drug Technology Center of Guangdong Province, Guangzhou, 510230, China.
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, 510515, China.
| | - Mengge Wang
- Institute of Rare Diseases, West China Hospital of Sichuan University, Sichuan University, Chengdu, 610041, China.
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510275, China.
- Anti-Drug Technology Center of Guangdong Province, Guangzhou, 510230, China.
- Research Center for Genomic Medicine, North Sichuan Medical College, Nanchong, 637100, China.
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Zhang Z, Jiang T, Li G, Cao S, Liu Y, Liu B, Wang Y. Kled: an ultra-fast and sensitive structural variant detection tool for long-read sequencing data. Brief Bioinform 2024; 25:bbae049. [PMID: 38385878 PMCID: PMC10883419 DOI: 10.1093/bib/bbae049] [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: 09/15/2023] [Revised: 01/12/2024] [Accepted: 01/26/2024] [Indexed: 02/23/2024] Open
Abstract
Structural Variants (SVs) are a crucial type of genetic variant that can significantly impact phenotypes. Therefore, the identification of SVs is an essential part of modern genomic analysis. In this article, we present kled, an ultra-fast and sensitive SV caller for long-read sequencing data given the specially designed approach with a novel signature-merging algorithm, custom refinement strategies and a high-performance program structure. The evaluation results demonstrate that kled can achieve optimal SV calling compared to several state-of-the-art methods on simulated and real long-read data for different platforms and sequencing depths. Furthermore, kled excels at rapid SV calling and can efficiently utilize multiple Central Processing Unit (CPU) cores while maintaining low memory usage. The source code for kled can be obtained from https://github.com/CoREse/kled.
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Affiliation(s)
- Zhendong Zhang
- Center for Bioinformatics, Faculty of Computing, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
- Key Laboratory of Biological Bigdata, Ministry of Education, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
| | - Tao Jiang
- Center for Bioinformatics, Faculty of Computing, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
- Zhengzhou Research Institute, Harbin Institute of Technology, Zhengzhou, Henan, 450000, China
- Key Laboratory of Biological Bigdata, Ministry of Education, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
| | - Gaoyang Li
- Center for Bioinformatics, Faculty of Computing, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
- Key Laboratory of Biological Bigdata, Ministry of Education, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
| | - Shuqi Cao
- Center for Bioinformatics, Faculty of Computing, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
- Key Laboratory of Biological Bigdata, Ministry of Education, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
| | - Yadong Liu
- Center for Bioinformatics, Faculty of Computing, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
- Zhengzhou Research Institute, Harbin Institute of Technology, Zhengzhou, Henan, 450000, China
- Key Laboratory of Biological Bigdata, Ministry of Education, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
| | - Bo Liu
- Center for Bioinformatics, Faculty of Computing, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
- Zhengzhou Research Institute, Harbin Institute of Technology, Zhengzhou, Henan, 450000, China
- Key Laboratory of Biological Bigdata, Ministry of Education, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
| | - Yadong Wang
- Center for Bioinformatics, Faculty of Computing, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
- Zhengzhou Research Institute, Harbin Institute of Technology, Zhengzhou, Henan, 450000, China
- Key Laboratory of Biological Bigdata, Ministry of Education, Harbin Institute of Technology, Harbin, Heilongjiang 150001, China
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Dokuru DR, Horwitz TB, Freis SM, Stallings MC, Ehringer MA. South Asia: The Missing Diverse in Diversity. Behav Genet 2024; 54:51-62. [PMID: 37917228 PMCID: PMC11129896 DOI: 10.1007/s10519-023-10161-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: 04/23/2023] [Accepted: 09/26/2023] [Indexed: 11/04/2023]
Abstract
South Asia, making up around 25% of the world's population, encompasses a wide range of individuals with tremendous genetic and environmental diversity. This region, which spans eight countries, is home to over 4500 anthropologically defined groups that speak numerous languages and have an array of religious beliefs and cultures, making it one of the most diverse places in the world. Much of the region's rich genetic diversity and structure is the result of a complex combination of population history, migration patterns, and endogamous practices. Despite the overwhelming size and diversity, South Asians have often been underrepresented in genetic research, making up less than 2% of the participants in genetic studies. This has led to a lack of population specific understanding of genetic disease risks. We aim to raise awareness about underlying genetic diversity in this ancestry group, call attention to the lack of representation of the group, and to highlight strategies for future studies in South Asians.
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Affiliation(s)
- Deepika R Dokuru
- Institute for Behavioral Genetics, University of Colorado Boulder, 1480 30 St, Boulder, CO, 80303, USA.
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA.
| | - Tanya B Horwitz
- Institute for Behavioral Genetics, University of Colorado Boulder, 1480 30 St, Boulder, CO, 80303, USA
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - Samantha M Freis
- Institute for Behavioral Genetics, University of Colorado Boulder, 1480 30 St, Boulder, CO, 80303, USA
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - Michael C Stallings
- Institute for Behavioral Genetics, University of Colorado Boulder, 1480 30 St, Boulder, CO, 80303, USA
- Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, USA
| | - Marissa A Ehringer
- Institute for Behavioral Genetics, University of Colorado Boulder, 1480 30 St, Boulder, CO, 80303, USA
- Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO, USA
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37
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Udupa P, Ghosh DK. Implementation of Exome Sequencing to Identify Rare Genetic Diseases. Methods Mol Biol 2024; 2719:79-98. [PMID: 37803113 DOI: 10.1007/978-1-0716-3461-5_5] [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] [Indexed: 10/08/2023]
Abstract
Modern high-throughput genomic testing using next-generation sequencing (NGS) has led to a significant increase in the successful diagnosis of rare genetic disorders. Recent advances in NGS tools and techniques have led to accurate and timely diagnosis of a large proportion of genetic diseases by finding sequence variations in clinical samples. One of the NGS techniques, exome sequencing (ES), is considered as a powerful and easily approachable method for genetic disorders in terms of rapid and cost-effective diagnostic yields. In this chapter, we describe an overview of whole exome sequencing (ES) in the context of experimental and analytical methodologies. Approaches to ES include sequencing capture technique, quality control processes at various stages of sequencing analysis, exome data filtering strategy that incorporates both primary and secondary filtering, and prioritization of candidate variants in diagnosing genetic diseases.
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Affiliation(s)
- Prajna Udupa
- Department of Medical Genetics, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, Karnataka, India
| | - Debasish Kumar Ghosh
- Enteric Disease Division, Department of Microbiology, Kasturba Medical College, Manipal Academy of Higher Education, Manipal, Karnataka, India
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38
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Xu J, Liu D, Hassan A, Genovese G, Cote AC, Fennessy B, Cheng E, Charney AW, Knowles JA, Ayub M, Peterson RE, Bigdeli TB, Huckins LM. Evaluation of imputation performance of multiple reference panels in a Pakistani population. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.22.23300448. [PMID: 38234809 PMCID: PMC10793543 DOI: 10.1101/2023.12.22.23300448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Genotype imputation is crucial for GWAS, but reference panels and existing benchmarking studies prioritize European individuals. Consequently, it is unclear which publicly available reference panel should be used for Pakistani individuals, and whether ancestry composition or sample size of the panel matters more for imputation accuracy. Our study compared different reference panels to impute genotype data in 1814 Pakistani individuals, finding the best performance balancing accuracy and coverage with meta-imputation with TOPMed and the expanded 1000 Genomes (ex1KG) reference. Imputation accuracy of ex1KG outperformed TOPMed despite its 30-fold smaller sample size, supporting efforts to create future panels with diverse populations.
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Affiliation(s)
- Jiayi Xu
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Dongjing Liu
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Arsalan Hassan
- University of Peshawar, Peshawar, Khyber Pakhtunkhwa, Pakistan
- Institute of Omics and Health Research, Lahore, Pakistan
| | - Giulio Genovese
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Alanna C. Cote
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Brian Fennessy
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Esther Cheng
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - James A. Knowles
- The Human Genetics Institute of New Jersey, Rutgers University, Piscataway, NJ, USA
| | | | - Roseann E. Peterson
- Department of Psychiatry and Behavioral Sciences, Institute for Genomics in Health, State University of New York Downstate Health Sciences University, Brooklyn, NY, USA
| | - Tim B. Bigdeli
- Department of Psychiatry and Behavioral Sciences, Institute for Genomics in Health, State University of New York Downstate Health Sciences University, Brooklyn, NY, USA
| | - Laura M. Huckins
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
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39
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Zhao Y, Zhong G, Hagen J, Pan H, Chung WK, Shen Y. A probabilistic graphical model for estimating selection coefficient of missense variants from human population sequence data. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.11.23299809. [PMID: 38168397 PMCID: PMC10760286 DOI: 10.1101/2023.12.11.23299809] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Accurately predicting the effect of missense variants is a central problem in interpretation of genomic variation. Commonly used computational methods does not capture the quantitative impact on fitness in populations. We developed MisFit to estimate missense fitness effect using biobank-scale human population genome data. MisFit jointly models the effect at molecular level ( d ) and population level (selection coefficient, s ), assuming that in the same gene, missense variants with similar d have similar s . MisFit is a probabilistic graphical model that integrates deep neural network components and population genetics models efficiently with inductive bias based on biological causality of variant effect. We trained it by maximizing probability of observed allele counts in 236,017 European individuals. We show that s is informative in predicting frequency across ancestries and consistent with the fraction of de novo mutations given s . Finally, MisFit outperforms previous methods in prioritizing missense variants in individuals with neurodevelopmental disorders.
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Affiliation(s)
- Yige Zhao
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032
- The Integrated Program in Cellular, Molecular, and Biomedical Studies, Columbia University, New York, NY 10032
| | - Guojie Zhong
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032
- The Integrated Program in Cellular, Molecular, and Biomedical Studies, Columbia University, New York, NY 10032
| | - Jake Hagen
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032
- Department of Pediatrics, Columbia University Irving Medical Center, New York, NY 10032
| | - Hongbing Pan
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY 10032
| | - Wendy K. Chung
- Department of Pediatrics, Boston Children’s Hospital and Harvard Medical School, Boston, MA 02115
| | - Yufeng Shen
- Department of Systems Biology, Columbia University Irving Medical Center, New York, NY 10032
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, NY 10032
- JP Sulzberger Columbia Genome Center, Columbia University, New York, NY 10032
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40
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Shenoy PU, Udupa H, KS J, Babu S, K N, Jain N, Das R, Upadhyai P. The impact of COVID-19 on pulmonary, neurological, and cardiac outcomes: evidence from a Mendelian randomization study. Front Public Health 2023; 11:1303183. [PMID: 38155884 PMCID: PMC10752946 DOI: 10.3389/fpubh.2023.1303183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 11/28/2023] [Indexed: 12/30/2023] Open
Abstract
Background Long COVID is a clinical entity characterized by persistent health problems or development of new diseases, without an alternative diagnosis, following SARS-CoV-2 infection that affects a significant proportion of individuals globally. It can manifest with a wide range of symptoms due to dysfunction of multiple organ systems including but not limited to cardiovascular, hematologic, neurological, gastrointestinal, and renal organs, revealed by observational studies. However, a causal association between the genetic predisposition to COVID-19 and many post-infective abnormalities in long COVID remain unclear. Methods Here we employed Mendelian randomization (MR), a robust genetic epidemiological approach, to investigate the potential causal associations between genetic predisposition to COVID-19 and long COVID symptoms, namely pulmonary (pneumonia and airway infections including bronchitis, emphysema, asthma, and rhinitis), neurological (headache, depression, and Parkinson's disease), cardiac (heart failure and chest pain) diseases, and chronic fatigue. Using two-sample MR, we leveraged genetic data from a large COVID-19 genome-wide association study and various disorder-specific datasets. Results This analysis revealed that a genetic predisposition to COVID-19 was significantly causally linked to an increased risk of developing pneumonia, airway infections, headache, and heart failure. It also showed a strong positive correlation with chronic fatigue, a frequently observed symptom in long COVID patients. However, our findings on Parkinson's disease, depression, and chest pain were inconclusive. Conclusion Overall, these findings provide valuable insights into the genetic underpinnings of long COVID and its diverse range of symptoms. Understanding these causal associations may aid in better management and treatment of long COVID patients, thereby alleviating the substantial burden it poses on global health and socioeconomic systems.
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Affiliation(s)
- Pooja U. Shenoy
- Division of Data Analytics, Bioinformatics and Structural Biology, Yenepoya Research Centre, Yenepoya (Deemed to be University), Mangalore, India
| | - Hrushikesh Udupa
- Department of Community Medicine, Yenepoya Medical College and Hospital, Yenepoya (Deemed to be University), Mangalore, India
| | - Jyothika KS
- Department of Statistics, Yenepoya (Deemed to be University), Mangalore, India
| | - Sangeetha Babu
- Department of Statistics, Yenepoya (Deemed to be University), Mangalore, India
| | - Nikshita K
- Department of Statistics, Yenepoya (Deemed to be University), Mangalore, India
| | - Neha Jain
- Department of Statistics, Yenepoya (Deemed to be University), Mangalore, India
| | - Ranajit Das
- Division of Data Analytics, Bioinformatics and Structural Biology, Yenepoya Research Centre, Yenepoya (Deemed to be University), Mangalore, India
| | - Priyanka Upadhyai
- Department of Medical Genetics, Kasturba Medical College, Manipal, Manipal Academy of Higher Education, Manipal, India
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Rabby MG, Rahman MH, Islam MN, Kamal MM, Biswas M, Bonny M, Hasan MM. In silico identification and functional prediction of differentially expressed genes in South Asian populations associated with type 2 diabetes. PLoS One 2023; 18:e0294399. [PMID: 38096208 PMCID: PMC10721103 DOI: 10.1371/journal.pone.0294399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Accepted: 11/01/2023] [Indexed: 12/17/2023] Open
Abstract
Type 2 diabetes (T2D) is one of the major metabolic disorders in humans caused by hyperglycemia and insulin resistance syndrome. Although significant genetic effects on T2D pathogenesis are experimentally proved, the molecular mechanism of T2D in South Asian Populations (SAPs) is still limited. Hence, the current research analyzed two Gene Expression Omnibus (GEO) and 17 Genome-Wide Association Studies (GWAS) datasets associated with T2D in SAP to identify DEGs (differentially expressed genes). The identified DEGs were further analyzed to explore the molecular mechanism of T2D pathogenesis following a series of bioinformatics approaches. Following PPI (Protein-Protein Interaction), 867 potential DEGs and nine hub genes were identified that might play significant roles in T2D pathogenesis. Interestingly, CTNNB1 and RUNX2 hub genes were found to be unique for T2D pathogenesis in SAPs. Then, the GO (Gene Ontology) showed the potential biological, molecular, and cellular functions of the DEGs. The target genes also interacted with different pathways of T2D pathogenesis. In fact, 118 genes (including HNF1A and TCF7L2 hub genes) were directly associated with T2D pathogenesis. Indeed, eight key miRNAs among 2582 significantly interacted with the target genes. Even 64 genes were downregulated by 367 FDA-approved drugs. Interestingly, 11 genes showed a wide range (9-43) of drug specificity. Hence, the identified DEGs may guide to elucidate the molecular mechanism of T2D pathogenesis in SAPs. Therefore, integrating the research findings of the potential roles of DEGs and candidate drug-mediated downregulation of marker genes, future drugs or treatments could be developed to treat T2D in SAPs.
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Affiliation(s)
- Md. Golam Rabby
- Department of Nutrition and Food Technology, Jashore University of Science and Technology, Khulna, Bangladesh
| | - Md. Hafizur Rahman
- Department of Agro Product Processing Technology, Jashore University of Science and Technology, Khulna, Bangladesh
- Faculty of Food Sciences and Safety, Department of Quality Control and Safety Management, Khulna Agricultural University, Khulna, Bangladesh
| | - Md. Numan Islam
- Department of Nutrition and Food Technology, Jashore University of Science and Technology, Khulna, Bangladesh
| | - Md. Mostafa Kamal
- Department of Nutrition and Food Technology, Jashore University of Science and Technology, Khulna, Bangladesh
| | - Mrityunjoy Biswas
- Department of Agro Product Processing Technology, Jashore University of Science and Technology, Khulna, Bangladesh
| | - Mantasa Bonny
- Department of Nutrition and Food Technology, Jashore University of Science and Technology, Khulna, Bangladesh
| | - Md. Mahmudul Hasan
- Department of Nutrition and Food Technology, Jashore University of Science and Technology, Khulna, Bangladesh
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Zee TW, Abdul Aziz MFB, Wei PC. Ethical challenges of conducting and reviewing human genomics research in Malaysia: An exploratory study. Dev World Bioeth 2023:10.1111/dewb.12435. [PMID: 37997006 PMCID: PMC11111594 DOI: 10.1111/dewb.12435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 10/17/2023] [Accepted: 10/24/2023] [Indexed: 11/25/2023]
Abstract
Even though there is a significant amount of scholarly work examining the ethical issues surrounding human genomics research, little is known about its footing in Malaysia. This study aims to explore the experience of local researchers and research ethics committee (REC) members in developing it in Malaysia. In-depth interviews were conducted from April to May 2021, and the data were thematically analysed. In advancing this technology, both genomics researchers and REC members have concerns over how this research is being developed in the country especially the absence of a clear ethical and regulatory framework at the national level as a guidance. However, this study argues that it is not a salient issue as there are international guidelines in existence and both researchers and RECs will benefit from a training on the guidelines to ensure genomics research can be developed in an ethical manner.
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Sulaieva ON, Artamonova O, Dudin O, Semikov R, Urakov D, Zakharash Y, Kacharian A, Strilka V, Mykhalchuk I, Haidamak O, Serdyukova O, Kobyliak N. Ethical navigation of biobanking establishment in Ukraine: learning from the experience of developing countries. JOURNAL OF MEDICAL ETHICS 2023:jme-2023-109129. [PMID: 37945338 DOI: 10.1136/jme-2023-109129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 10/28/2023] [Indexed: 11/12/2023]
Abstract
Building a biobank network in developing countries is essential to foster genomic research and precision medicine for patients' benefit. However, there are serious barriers to establishing biobanks in low-income and middle-income countries (LMICs), including Ukraine. Here, we outline key barriers and essential milestones for the successful expansion of biobanks, genomic research and personalised medicine in Ukraine, drawing from the experience of other LMICs. A lack of legal and ethical governance in conjunction with limited awareness about biobanking and community distrust are the principal threats to establishing biobanks. The experiences of LMICs suggest that Ukraine urgently needs national guidelines covering ethical and legal aspects of biospecimen-related research. National guidelines must be consistent with international ethical recommendations for safeguarding participants' rights, welfare and privacy. Additionally, efforts to educate and engage physicians and patient communities are essential for achieving biobanking goals and benefits for precision medicine and future patients.
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Affiliation(s)
- Oksana N Sulaieva
- Department of Pathology, Medical Laboratory CSD, Kyiv, Ukraine
- Doctorate in Bioethics, Neiswanger Institute for Bioethics, Loyola University Chicago, Chicago, Illinois, USA
- Ukrainian Association of Research Biobanks, Kyiv, Ukraine
| | | | - Oleksandr Dudin
- Department of Pathology, Medical Laboratory CSD, Kyiv, Ukraine
| | - Rostyslav Semikov
- Ukrainian Association of Research Biobanks, Kyiv, Ukraine
- Audubon Bioscience, Kyiv, Ukraine
| | - Dmytro Urakov
- Ukrainian Association of Research Biobanks, Kyiv, Ukraine
| | | | | | | | - Ivan Mykhalchuk
- Ukrainian Association of Research Biobanks, Kyiv, Ukraine
- Audubon Bioscience, Kyiv, Ukraine
| | | | - Olena Serdyukova
- Ukrainian Association of Research Biobanks, Kyiv, Ukraine
- Audubon Bioscience, Kyiv, Ukraine
| | - Nazarii Kobyliak
- Department of Pathology, Medical Laboratory CSD, Kyiv, Ukraine
- Department of Endocrinology, Bogomolets National Medical University, Kyiv, Ukraine
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44
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Gouveia MH, Bentley AR, Leal TP, Tarazona-Santos E, Bustamante CD, Adeyemo AA, Rotimi CN, Shriner D. Unappreciated subcontinental admixture in Europeans and European Americans and implications for genetic epidemiology studies. Nat Commun 2023; 14:6802. [PMID: 37935687 PMCID: PMC10630423 DOI: 10.1038/s41467-023-42491-0] [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: 03/16/2023] [Accepted: 10/12/2023] [Indexed: 11/09/2023] Open
Abstract
European-ancestry populations are recognized as stratified but not as admixed, implying that residual confounding by locus-specific ancestry can affect studies of association, polygenic adaptation, and polygenic risk scores. We integrate individual-level genome-wide data from ~19,000 European-ancestry individuals across 79 European populations and five European American cohorts. We generate a new reference panel that captures ancestral diversity missed by both the 1000 Genomes and Human Genome Diversity Projects. Both Europeans and European Americans are admixed at the subcontinental level, with admixture dates differing among subgroups of European Americans. After adjustment for both genome-wide and locus-specific ancestry, associations between a highly differentiated variant in LCT (rs4988235) and height or LDL-cholesterol were confirmed to be false positives whereas the association between LCT and body mass index was genuine. We provide formal evidence of subcontinental admixture in individuals with European ancestry, which, if not properly accounted for, can produce spurious results in genetic epidemiology studies.
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Affiliation(s)
- Mateus H Gouveia
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Thiago P Leal
- Department of Genomic Medicine, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, 44197, USA
| | - Eduardo Tarazona-Santos
- Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, 31270-910, Brazil
| | - Carlos D Bustamante
- Center for Computational, Evolutionary and Human Genomics (CEHG), Stanford University, Stanford, CA, 94305, USA
| | - Adebowale A Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA
| | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
| | - Daniel Shriner
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
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45
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Sun KY, Bai X, Chen S, Bao S, Kapoor M, Zhang C, Backman J, Joseph T, Maxwell E, Mitra G, Gorovits A, Mansfield A, Boutkov B, Gokhale S, Habegger L, Marcketta A, Locke A, Kessler MD, Sharma D, Staples J, Bovijn J, Gelfman S, Gioia AD, Rajagopal V, Lopez A, Varela JR, Alegre J, Berumen J, Tapia-Conyer R, Kuri-Morales P, Torres J, Emberson J, Collins R, Cantor M, Thornton T, Kang HM, Overton J, Shuldiner AR, Cremona ML, Nafde M, Baras A, Abecasis G, Marchini J, Reid JG, Salerno W, Balasubramanian S. A deep catalog of protein-coding variation in 985,830 individuals. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.09.539329. [PMID: 37214792 PMCID: PMC10197621 DOI: 10.1101/2023.05.09.539329] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Coding variants that have significant impact on function can provide insights into the biology of a gene but are typically rare in the population. Identifying and ascertaining the frequency of such rare variants requires very large sample sizes. Here, we present the largest catalog of human protein-coding variation to date, derived from exome sequencing of 985,830 individuals of diverse ancestry to serve as a rich resource for studying rare coding variants. Individuals of African, Admixed American, East Asian, Middle Eastern, and South Asian ancestry account for 20% of this Exome dataset. Our catalog of variants includes approximately 10.5 million missense (54% novel) and 1.1 million predicted loss-of-function (pLOF) variants (65% novel, 53% observed only once). We identified individuals with rare homozygous pLOF variants in 4,874 genes, and for 1,838 of these this work is the first to document at least one pLOF homozygote. Additional insights from the RGC-ME dataset include 1) improved estimates of selection against heterozygous loss-of-function and identification of 3,459 genes intolerant to loss-of-function, 83 of which were previously assessed as tolerant to loss-of-function and 1,241 that lack disease annotations; 2) identification of regions depleted of missense variation in 457 genes that are tolerant to loss-of-function; 3) functional interpretation for 10,708 variants of unknown or conflicting significance reported in ClinVar as cryptic splice sites using splicing score thresholds based on empirical variant deleteriousness scores derived from RGC-ME; and 4) an observation that approximately 3% of sequenced individuals carry a clinically actionable genetic variant in the ACMG SF 3.1 list of genes. We make this important resource of coding variation available to the public through a variant allele frequency browser. We anticipate that this report and the RGC-ME dataset will serve as a valuable reference for understanding rare coding variation and help advance precision medicine efforts.
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Affiliation(s)
| | | | - Siying Chen
- Regeneron Genetics Center, Tarrytown, NY, USA
| | - Suying Bao
- Regeneron Genetics Center, Tarrytown, NY, USA
| | | | | | | | | | | | | | | | | | | | | | | | | | - Adam Locke
- Regeneron Genetics Center, Tarrytown, NY, USA
| | | | | | | | | | | | | | | | | | | | - Jesus Alegre
- Experimental Research Unit from the Faculty of Medicine (UIME), National Autonomous University of Mexico (UNAM)
| | - Jaime Berumen
- Experimental Research Unit from the Faculty of Medicine (UIME), National Autonomous University of Mexico (UNAM)
| | - Roberto Tapia-Conyer
- Experimental Research Unit from the Faculty of Medicine (UIME), National Autonomous University of Mexico (UNAM)
| | - Pablo Kuri-Morales
- Experimental Research Unit from the Faculty of Medicine (UIME), National Autonomous University of Mexico (UNAM)
| | - Jason Torres
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Jonathan Emberson
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Rory Collins
- Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | | | | | | | | | | | | | | | | | - Mona Nafde
- Regeneron Genetics Center, Tarrytown, NY, USA
| | - Aris Baras
- Regeneron Genetics Center, Tarrytown, NY, USA
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46
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Cahoon JL, Rui X, Tang E, Simons C, Langie J, Chen M, Lo YC, Chiang CWK. Imputation Accuracy Across Global Human Populations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.22.541241. [PMID: 37292811 PMCID: PMC10245797 DOI: 10.1101/2023.05.22.541241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Genotype imputation is now fundamental for genome-wide association studies but lacks fairness due to the underrepresentation of populations with non-European ancestries. The state-of-the-art imputation reference panel released by the Trans-Omics for Precision Medicine (TOPMed) initiative contains a substantial number of admixed African-ancestry and Hispanic/Latino samples to impute these populations with nearly the same accuracy as European-ancestry cohorts. However, imputation for populations primarily residing outside of North America may still fall short in performance due to persisting underrepresentation. To illustrate this point, we curated genome-wide array data from 23 publications published between 2008 to 2021. In total, we imputed over 43k individuals across 123 populations around the world. We identified a number of populations where imputation accuracy paled in comparison to that of European-ancestry populations. For instance, the mean imputation r-squared (Rsq) for 1-5% alleles in Saudi Arabians (N=1061), Vietnamese (N=1264), Thai (N=2435), and Papua New Guineans (N=776) were 0.79, 0.78, 0.76, and 0.62, respectively. In contrast, the mean Rsq ranged from 0.90 to 0.93 for comparable European populations matched in sample size and SNP content. Outside of Africa and Latin America, Rsq appeared to decrease as genetic distances to European reference increased, as predicted. Further analysis using sequencing data as ground truth suggested that imputation software may over-estimate imputation accuracy for non-European populations than European populations, suggesting further disparity between populations. Using 1496 whole genome sequenced individuals from Taiwan Biobank as a reference, we also assessed a strategy to improve imputation for non-European populations with meta-imputation, which can combine results from TOPMed with smaller population-specific reference panels. We found that meta-imputation in this design did not improve Rsq genome-wide. Taken together, our analysis suggests that with the current size of alternative reference panels, meta-imputation alone cannot improve imputation efficacy for underrepresented cohorts and we must ultimately strive to increase diversity and size to promote equity within genetics research.
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Affiliation(s)
- Jordan L. Cahoon
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA
- Department of Computer Science, University of Southern California, Los Angeles, CA 90089, USA
| | - Xinyue Rui
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Echo Tang
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA
| | - Christopher Simons
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA
| | - Jalen Langie
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Minhui Chen
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Ying-Chu Lo
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Charleston W. K. Chiang
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
- Department of Quantitative and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA
- Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA
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47
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Liu X, Matsunami M, Horikoshi M, Ito S, Ishikawa Y, Suzuki K, Momozawa Y, Niida S, Kimura R, Ozaki K, Maeda S, Imamura M, Terao C. Natural Selection Signatures in the Hondo and Ryukyu Japanese Subpopulations. Mol Biol Evol 2023; 40:msad231. [PMID: 37903429 PMCID: PMC10615566 DOI: 10.1093/molbev/msad231] [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: 03/27/2023] [Revised: 09/20/2023] [Accepted: 10/06/2023] [Indexed: 11/01/2023] Open
Abstract
Natural selection signatures across Japanese subpopulations are under-explored. Here we conducted genome-wide selection scans with 622,926 single nucleotide polymorphisms for 20,366 Japanese individuals, who were recruited from the main-islands of Japanese Archipelago (Hondo) and the Ryukyu Archipelago (Ryukyu), representing two major Japanese subpopulations. The integrated haplotype score (iHS) analysis identified several signals in one or both subpopulations. We found a novel candidate locus at IKZF2, especially in Ryukyu. Significant signals were observed in the major histocompatibility complex region in both subpopulations. The lead variants differed and demonstrated substantial allele frequency differences between Hondo and Ryukyu. The lead variant in Hondo tags HLA-A*33:03-C*14:03-B*44:03-DRB1*13:02-DQB1*06:04-DPB1*04:01, a haplotype specific to Japanese and Korean. While in Ryukyu, the lead variant tags DRB1*15:01-DQB1*06:02, which had been recognized as a genetic risk factor for narcolepsy. In contrast, it is reported to confer protective effects against type 1 diabetes and human T lymphotropic virus type 1-associated myelopathy/tropical spastic paraparesis. The FastSMC analysis identified 8 loci potentially affected by selection within the past 20-150 generations, including 2 novel candidate loci. The analysis also showed differences in selection patterns of ALDH2 between Hondo and Ryukyu, a gene recognized to be specifically targeted by selection in East Asian. In summary, our study provided insights into the selection signatures within the Japanese and nominated potential sources of selection pressure.
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Affiliation(s)
- Xiaoxi Liu
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
| | - Masatoshi Matsunami
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Nishihara-Cho, Japan
| | - Momoko Horikoshi
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Shuji Ito
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yuki Ishikawa
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Kunihiko Suzuki
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Shumpei Niida
- Core Facility Administration, Research Institute, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Ryosuke Kimura
- Department of Human Biology and Anatomy, Graduate School of Medicine, University of the Ryukyus, Nishihara-Cho, Japan
| | - Kouichi Ozaki
- Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Shiro Maeda
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Nishihara-Cho, Japan
- Division of Clinical Laboratory and Blood Transfusion, University of the Ryukyus Hospital, Okinawa, Japan
| | - Minako Imamura
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Nishihara-Cho, Japan
- Division of Clinical Laboratory and Blood Transfusion, University of the Ryukyus Hospital, Okinawa, Japan
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
- The Department of Applied Genetics, School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
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48
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Yang C, Zhou Y, Song Y, Wu D, Zeng Y, Nie L, Liu P, Zhang S, Chen G, Xu J, Zhou H, Zhou L, Qian X, Liu C, Tan S, Zhou C, Dai W, Xu M, Qi Y, Wang X, Guo L, Fan G, Wang A, Deng Y, Zhang Y, Jin J, He Y, Guo C, Guo G, Zhou Q, Xu X, Yang H, Wang J, Xu S, Mao Y, Jin X, Ruan J, Zhang G. The complete and fully-phased diploid genome of a male Han Chinese. Cell Res 2023; 33:745-761. [PMID: 37452091 PMCID: PMC10542383 DOI: 10.1038/s41422-023-00849-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Accepted: 06/29/2023] [Indexed: 07/18/2023] Open
Abstract
Since the release of the complete human genome, the priority of human genomic study has now been shifting towards closing gaps in ethnic diversity. Here, we present a fully phased and well-annotated diploid human genome from a Han Chinese male individual (CN1), in which the assemblies of both haploids achieve the telomere-to-telomere (T2T) level. Comparison of this diploid genome with the CHM13 haploid T2T genome revealed significant variations in the centromere. Outside the centromere, we discovered 11,413 structural variations, including numerous novel ones. We also detected thousands of CN1 alleles that have accumulated high substitution rates and a few that have been under positive selection in the East Asian population. Further, we found that CN1 outperforms CHM13 as a reference genome in mapping and variant calling for the East Asian population owing to the distinct structural variants of the two references. Comparison of SNP calling for a large cohort of 8869 Chinese genomes using CN1 and CHM13 as reference respectively showed that the reference bias profoundly impacts rare SNP calling, with nearly 2 million rare SNPs miss-called with different reference genomes. Finally, applying the CN1 as a reference, we discovered 5.80 Mb and 4.21 Mb putative introgression sequences from Neanderthal and Denisovan, respectively, including many East Asian specific ones undetected using CHM13 as the reference. Our analyses reveal the advances of using CN1 as a reference for population genomic studies and paleo-genomic studies. This complete genome will serve as an alternative reference for future genomic studies on the East Asian population.
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Affiliation(s)
- Chentao Yang
- Center for Genomic Research, International Institutes of Medicine, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, Zhejiang, China
- Center for Evolutionary & Organismal Biology, & Women's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- BGI-Shenzhen, Shenzhen, Guangdong, China
| | - Yang Zhou
- BGI-Shenzhen, Shenzhen, Guangdong, China
- BGI Research-Wuhan, BGI, Wuhan, Hubei, China
| | - Yanni Song
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Dongya Wu
- Center for Genomic Research, International Institutes of Medicine, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, Zhejiang, China
- Center for Evolutionary & Organismal Biology, & Women's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, Zhejiang, China
- Institute of Crop Science & Institute of Bioinformatics, Zhejiang University, Hangzhou, Zhejiang, China
| | - Yan Zeng
- BGI-Shenzhen, Shenzhen, Guangdong, China
| | - Lei Nie
- BGI-Shenzhen, Shenzhen, Guangdong, China
| | | | - Shilong Zhang
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Guangji Chen
- BGI-Shenzhen, Shenzhen, Guangdong, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Jinjin Xu
- BGI-Shenzhen, Shenzhen, Guangdong, China
| | - Hongling Zhou
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Long Zhou
- Center for Evolutionary & Organismal Biology, & Women's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, Zhejiang, China
- Innovation Center of Yangtze River Delta, Zhejiang University, Hangzhou, Zhejiang, China
| | - Xiaobo Qian
- BGI-Shenzhen, Shenzhen, Guangdong, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Chenlu Liu
- Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang, China
| | | | | | - Wei Dai
- BGI-Shenzhen, Shenzhen, Guangdong, China
| | - Mengyang Xu
- BGI-Shenzhen, Shenzhen, Guangdong, China
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong, China
| | - Yanwei Qi
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong, China
| | - Xiaobo Wang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China
| | - Lidong Guo
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong, China
| | - Guangyi Fan
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong, China
| | - Aijun Wang
- BGI-Qingdao, BGI-Shenzhen, Qingdao, Shandong, China
| | - Yuan Deng
- BGI-Shenzhen, Shenzhen, Guangdong, China
| | - Yong Zhang
- BGI-Shenzhen, Shenzhen, Guangdong, China
| | | | - Yunqiu He
- Center for Genomic Research, International Institutes of Medicine, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, Zhejiang, China
- Center for Evolutionary & Organismal Biology, & Women's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Chunxue Guo
- BGI-Shenzhen, Shenzhen, Guangdong, China
- BGI-Hangzhou, Hangzhou, Zhejiang, China
| | - Guoji Guo
- School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Qing Zhou
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, Zhejiang, China
- Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang, China
| | - Xun Xu
- BGI-Shenzhen, Shenzhen, Guangdong, China
| | | | - Jian Wang
- BGI-Shenzhen, Shenzhen, Guangdong, China
| | - Shuhua Xu
- State Key Laboratory of Genetic Engineering, Center for Evolutionary Biology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
- Human Phenome Institute, Zhangjiang Fudan International Innovation Center, and Ministry of Education Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai, China
- Jiangsu Key Laboratory of Phylogenomics & Comparative Genomics, International Joint Center of Genomics of Jiangsu Province School of Life Sciences, Jiangsu Normal University, Xuzhou, Jiangsu, China
- Department of Liver Surgery and Transplantation Liver Cancer Institute, Zhongshan Hospital, Fudan University, Shanghai, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Yafei Mao
- Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Ministry of Education, Shanghai Jiao Tong University, Shanghai, China
| | - Xin Jin
- BGI-Shenzhen, Shenzhen, Guangdong, China
| | - Jue Ruan
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China.
| | - Guojie Zhang
- Center for Genomic Research, International Institutes of Medicine, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, Zhejiang, China.
- Center for Evolutionary & Organismal Biology, & Women's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, Zhejiang, China.
- Innovation Center of Yangtze River Delta, Zhejiang University, Hangzhou, Zhejiang, China.
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.
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49
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Joshi E, Biddanda A, Popoola J, Yakubu A, Osakwe O, Attipoe D, Dogbo E, Salako B, Nash O, Salako O, Oyedele O, Eze-Echesi G, Fatumo S, Ene-Obong A, O’Dushlaine C. Whole-genome sequencing across 449 samples spanning 47 ethnolinguistic groups provides insights into genetic diversity in Nigeria. CELL GENOMICS 2023; 3:100378. [PMID: 37719143 PMCID: PMC10504631 DOI: 10.1016/j.xgen.2023.100378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 02/23/2023] [Accepted: 07/13/2023] [Indexed: 09/19/2023]
Abstract
African populations have been drastically underrepresented in genomics research, and failure to capture the genetic diversity across the numerous ethnolinguistic groups (ELGs) found on the continent has hindered the equity of precision medicine initiatives globally. Here, we describe the whole-genome sequencing of 449 Nigerian individuals across 47 unique self-reported ELGs. Population structure analysis reveals genetic differentiation among our ELGs, consistent with previous findings. From the 36 million SNPs and insertions or deletions (indels) discovered in our dataset, we provide a high-level catalog of both novel and medically relevant variation present across the ELGs. These results emphasize the value of this resource for genomics research, with added granularity by representing multiple ELGs from Nigeria. Our results also underscore the potential of using these cohorts with larger sample sizes to improve our understanding of human ancestry and health in Africa.
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Affiliation(s)
- Esha Joshi
- 54gene, Inc., 1100 15th St. NW, Washington, DC 20005, USA
| | - Arjun Biddanda
- 54gene, Inc., 1100 15th St. NW, Washington, DC 20005, USA
| | - Jumi Popoola
- 54gene, Inc., 1100 15th St. NW, Washington, DC 20005, USA
| | - Aminu Yakubu
- 54gene, Inc., 1100 15th St. NW, Washington, DC 20005, USA
| | | | - Delali Attipoe
- 54gene, Inc., 1100 15th St. NW, Washington, DC 20005, USA
| | - Estelle Dogbo
- 54gene, Inc., 1100 15th St. NW, Washington, DC 20005, USA
| | | | - Oyekanmi Nash
- Center for Genomics Research and Innovation, National Agency for Biotechnology Development, Abuja 09004, Nigeria
- H3Africa Bioinformatics Network (H3ABioNet) Node, Centre for Genomics Research and Innovation, NABDA/FMST, Abuja 09004, Nigeria
| | - Omolola Salako
- College of Medicine University of Lagos, Lagos 101233, Nigeria
| | | | | | - Segun Fatumo
- H3Africa Bioinformatics Network (H3ABioNet) Node, Centre for Genomics Research and Innovation, NABDA/FMST, Abuja 09004, Nigeria
- The African Computational Genomics (TAGC) Research Group, MRC/UVRI and London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK
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50
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Sanga S, Chakraborty S, Bardhan M, Polavarapu K, Kumar VP, Bhattacharya C, Nashi S, Vengalil S, Geetha TS, Ramprasad V, Nalini A, Basu A, Acharya M. Identification of a shared, common haplotype segregating with an SGCB c.544 T > G mutation in Indian patients affected with sarcoglycanopathy. Sci Rep 2023; 13:15095. [PMID: 37699968 PMCID: PMC10497502 DOI: 10.1038/s41598-023-41487-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 08/28/2023] [Indexed: 09/14/2023] Open
Abstract
Sarcoglycanopathy is the most frequent form of autosomal recessive limb-girdle muscular dystrophies caused by mutations in SGCB gene encoding beta-sarcoglycan proteins. In this study, we describe a shared, common haplotype co-segregating in 14 sarcoglycanopathy cases from 13 unrelated families from south Indian region with the likely pathogenic homozygous mutation c.544 T > G (p.Thr182Pro) in SGCB. Haplotype was reconstructed based on 10 polymorphic markers surrounding the c.544 T > G mutation in the cases and related family members as well as 150 unrelated controls from Indian populations using PLINK1.9. We identified haplotype H1 = G, A, G, T, G, G, A, C, T, G, T at a significantly higher frequency in cases compared to related controls and unrelated control Indian population. Upon segregation analysis within the family pedigrees, H1 is observed to co-segregate with c.544 T > G in a homozygous state in all the pedigrees of cases except one indicating a probable event of founder effect. Furthermore, Identical-by-descent and inbreeding coefficient analysis revealed relatedness among 33 new pairs of seemingly unrelated individuals from sarcoglycanopathy cohort and a higher proportion of homozygous markers, thereby indicating common ancestry. Since all these patients are from the south Indian region, we suggest this region to be a primary target of mutation screening in patients diagnosed with sarcoglycanopathy.
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Affiliation(s)
- Shamita Sanga
- National Institute of Biomedical Genomics, P.O: N.S.S, Kalyani, West Bengal, 741251, India
| | - Sudipta Chakraborty
- National Institute of Biomedical Genomics, P.O: N.S.S, Kalyani, West Bengal, 741251, India
- Regional Centre for Biotechnology, Faridabad, India
| | - Mainak Bardhan
- National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Kiran Polavarapu
- National Institute of Mental Health and Neurosciences, Bangalore, India
| | | | - Chandrika Bhattacharya
- National Institute of Biomedical Genomics, P.O: N.S.S, Kalyani, West Bengal, 741251, India
| | - Saraswati Nashi
- National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Seena Vengalil
- National Institute of Mental Health and Neurosciences, Bangalore, India
| | | | | | - Atchayaram Nalini
- National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Analabha Basu
- National Institute of Biomedical Genomics, P.O: N.S.S, Kalyani, West Bengal, 741251, India
| | - Moulinath Acharya
- National Institute of Biomedical Genomics, P.O: N.S.S, Kalyani, West Bengal, 741251, India.
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