Pub Date : 2024-11-11DOI: 10.1038/s41588-024-01974-6
Helen Dimaras, Beatrice Omweri, Daniel Muema, Loice Kanda, Rosaline Wanjiru Macharia, John Gitau, Catherine Mutinda, Kahaki Kimani, Wairimu Waweru, Stephen Gichuhi, Marianne W. Mureithi, Lucy Njambi
Despite extensive advancements in cancer genetics in North America and Europe, the African continent remains underrepresented in this vital research area. Here we highlight a pioneering collaborative project in Kenya, with a focus on expanding cancer genetics services and research into retinoblastoma, a prototypical heritable cancer syndrome.
{"title":"Toward advances in retinoblastoma genetics in Kenya","authors":"Helen Dimaras, Beatrice Omweri, Daniel Muema, Loice Kanda, Rosaline Wanjiru Macharia, John Gitau, Catherine Mutinda, Kahaki Kimani, Wairimu Waweru, Stephen Gichuhi, Marianne W. Mureithi, Lucy Njambi","doi":"10.1038/s41588-024-01974-6","DOIUrl":"10.1038/s41588-024-01974-6","url":null,"abstract":"Despite extensive advancements in cancer genetics in North America and Europe, the African continent remains underrepresented in this vital research area. Here we highlight a pioneering collaborative project in Kenya, with a focus on expanding cancer genetics services and research into retinoblastoma, a prototypical heritable cancer syndrome.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"56 12","pages":"2585-2588"},"PeriodicalIF":31.7,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142598339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-11DOI: 10.1038/s41588-024-01973-7
Ciyang Wang, Chengran Yang, Daniel Western, Muhammad Ali, Yueyao Wang, Chia-Ling Phuah, John Budde, Lihua Wang, Priyanka Gorijala, Jigyasha Timsina, Agustin Ruiz, Pau Pastor, Maria Victoria Fernandez, Dominantly Inherited Alzheimer Network (DIAN), The Alzheimer’s Disease Neuroimaging Initiative (ADNI), Daniel J. Panyard, Corinne D. Engelman, Yuetiva Deming, Merce Boada, Amanda Cano, Pablo Garcia-Gonzalez, Neill R. Graff-Radford, Hiroshi Mori, Jae-Hong Lee, Richard J. Perrin, Laura Ibanez, Yun Ju Sung, Carlos Cruchaga
Brain metabolism perturbation can contribute to traits and diseases. We conducted a genome-wide association study for cerebrospinal fluid (CSF) and brain metabolite levels, identifying 205 independent associations (47.3% new signals, containing 11 new loci) for 139 CSF metabolites, and 32 independent associations (43.8% new signals, containing 4 new loci) for 31 brain metabolites. Of these, 96.9% (CSF) and 71.4% (brain) of the new signals belonged to previously analyzed metabolites in blood or urine. We integrated the metabolite quantitative trait loci (MQTLs) with 23 neurological, psychiatric and common human traits and diseases through colocalization to identify metabolites and biological processes implicated in these phenotypes. Combining CSF and brain, we identified 71 metabolite–trait associations, such as glycerophosphocholines with Alzheimer’s disease, O-sulfo-l-tyrosine with Parkinson’s disease, glycine, xanthine with waist-to-hip ratio and ergothioneine with inflammatory bowel disease. Our study expanded the knowledge of MQTLs in the central nervous system, providing insights into human traits. Genome-wide association study of cerebrospinal fluid and brain metabolites highlights the unique genetic architecture of metabolite levels and metabolite–trait associations with brain-related phenotypes.
{"title":"Genetic architecture of cerebrospinal fluid and brain metabolite levels and the genetic colocalization of metabolites with human traits","authors":"Ciyang Wang, Chengran Yang, Daniel Western, Muhammad Ali, Yueyao Wang, Chia-Ling Phuah, John Budde, Lihua Wang, Priyanka Gorijala, Jigyasha Timsina, Agustin Ruiz, Pau Pastor, Maria Victoria Fernandez, Dominantly Inherited Alzheimer Network (DIAN), The Alzheimer’s Disease Neuroimaging Initiative (ADNI), Daniel J. Panyard, Corinne D. Engelman, Yuetiva Deming, Merce Boada, Amanda Cano, Pablo Garcia-Gonzalez, Neill R. Graff-Radford, Hiroshi Mori, Jae-Hong Lee, Richard J. Perrin, Laura Ibanez, Yun Ju Sung, Carlos Cruchaga","doi":"10.1038/s41588-024-01973-7","DOIUrl":"10.1038/s41588-024-01973-7","url":null,"abstract":"Brain metabolism perturbation can contribute to traits and diseases. We conducted a genome-wide association study for cerebrospinal fluid (CSF) and brain metabolite levels, identifying 205 independent associations (47.3% new signals, containing 11 new loci) for 139 CSF metabolites, and 32 independent associations (43.8% new signals, containing 4 new loci) for 31 brain metabolites. Of these, 96.9% (CSF) and 71.4% (brain) of the new signals belonged to previously analyzed metabolites in blood or urine. We integrated the metabolite quantitative trait loci (MQTLs) with 23 neurological, psychiatric and common human traits and diseases through colocalization to identify metabolites and biological processes implicated in these phenotypes. Combining CSF and brain, we identified 71 metabolite–trait associations, such as glycerophosphocholines with Alzheimer’s disease, O-sulfo-l-tyrosine with Parkinson’s disease, glycine, xanthine with waist-to-hip ratio and ergothioneine with inflammatory bowel disease. Our study expanded the knowledge of MQTLs in the central nervous system, providing insights into human traits. Genome-wide association study of cerebrospinal fluid and brain metabolites highlights the unique genetic architecture of metabolite levels and metabolite–trait associations with brain-related phenotypes.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"56 12","pages":"2685-2695"},"PeriodicalIF":31.7,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142598340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-11DOI: 10.1038/s41588-024-01972-8
Daniel Western, Jigyasha Timsina, Lihua Wang, Ciyang Wang, Chengran Yang, Bridget Phillips, Yueyao Wang, Menghan Liu, Muhammad Ali, Aleksandra Beric, Priyanka Gorijala, Pat Kohlfeld, John Budde, Allan I. Levey, John C. Morris, Richard J. Perrin, Agustin Ruiz, Marta Marquié, Mercè Boada, Itziar de Rojas, Jarod Rutledge, Hamilton Oh, Edward N. Wilson, Yann Le Guen, Lianne M. Reus, Betty Tijms, Pieter Jelle Visser, Sven J. van der Lee, Yolande A. L. Pijnenburg, Charlotte E. Teunissen, Marta del Campo Milan, Ignacio Alvarez, Miquel Aguilar, Dominantly Inherited Alzheimer Network (DIAN), the Alzheimer’s Disease Neuroimaging Initiative (ADNI), Michael D. Greicius, Pau Pastor, David J. Pulford, Laura Ibanez, Tony Wyss-Coray, Yun Ju Sung, Carlos Cruchaga
The integration of quantitative trait loci (QTLs) with disease genome-wide association studies (GWASs) has proven successful in prioritizing candidate genes at disease-associated loci. QTL mapping has been focused on multi-tissue expression QTLs or plasma protein QTLs (pQTLs). We generated a cerebrospinal fluid (CSF) pQTL atlas by measuring 6,361 proteins in 3,506 samples. We identified 3,885 associations for 1,883 proteins, including 2,885 new pQTLs, demonstrating unique genetic regulation in CSF. We identified CSF-enriched pleiotropic regions on chromosome (chr)3q28 near OSTN and chr19q13.32 near APOE that were enriched for neuron specificity and neurological development. We integrated our associations with Alzheimer’s disease (AD) through proteome-wide association study (PWAS), colocalization and Mendelian randomization and identified 38 putative causal proteins, 15 of which have drugs available. Finally, we developed a proteomics-based AD prediction model that outperforms genetics-based models. These findings will be instrumental to further understand the biology and identify causal and druggable proteins for brain and neurological traits. Proteogenomic analysis of human cerebrospinal fluid by measuring 6,361 proteins in 3,506 individuals identifies new protein QTLs and highlights genetic regulation involved in neurological processes.
{"title":"Proteogenomic analysis of human cerebrospinal fluid identifies neurologically relevant regulation and implicates causal proteins for Alzheimer’s disease","authors":"Daniel Western, Jigyasha Timsina, Lihua Wang, Ciyang Wang, Chengran Yang, Bridget Phillips, Yueyao Wang, Menghan Liu, Muhammad Ali, Aleksandra Beric, Priyanka Gorijala, Pat Kohlfeld, John Budde, Allan I. Levey, John C. Morris, Richard J. Perrin, Agustin Ruiz, Marta Marquié, Mercè Boada, Itziar de Rojas, Jarod Rutledge, Hamilton Oh, Edward N. Wilson, Yann Le Guen, Lianne M. Reus, Betty Tijms, Pieter Jelle Visser, Sven J. van der Lee, Yolande A. L. Pijnenburg, Charlotte E. Teunissen, Marta del Campo Milan, Ignacio Alvarez, Miquel Aguilar, Dominantly Inherited Alzheimer Network (DIAN), the Alzheimer’s Disease Neuroimaging Initiative (ADNI), Michael D. Greicius, Pau Pastor, David J. Pulford, Laura Ibanez, Tony Wyss-Coray, Yun Ju Sung, Carlos Cruchaga","doi":"10.1038/s41588-024-01972-8","DOIUrl":"10.1038/s41588-024-01972-8","url":null,"abstract":"The integration of quantitative trait loci (QTLs) with disease genome-wide association studies (GWASs) has proven successful in prioritizing candidate genes at disease-associated loci. QTL mapping has been focused on multi-tissue expression QTLs or plasma protein QTLs (pQTLs). We generated a cerebrospinal fluid (CSF) pQTL atlas by measuring 6,361 proteins in 3,506 samples. We identified 3,885 associations for 1,883 proteins, including 2,885 new pQTLs, demonstrating unique genetic regulation in CSF. We identified CSF-enriched pleiotropic regions on chromosome (chr)3q28 near OSTN and chr19q13.32 near APOE that were enriched for neuron specificity and neurological development. We integrated our associations with Alzheimer’s disease (AD) through proteome-wide association study (PWAS), colocalization and Mendelian randomization and identified 38 putative causal proteins, 15 of which have drugs available. Finally, we developed a proteomics-based AD prediction model that outperforms genetics-based models. These findings will be instrumental to further understand the biology and identify causal and druggable proteins for brain and neurological traits. Proteogenomic analysis of human cerebrospinal fluid by measuring 6,361 proteins in 3,506 individuals identifies new protein QTLs and highlights genetic regulation involved in neurological processes.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"56 12","pages":"2672-2684"},"PeriodicalIF":31.7,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142598343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-11DOI: 10.1038/s41588-024-01958-6
Carman Man-Chung Li, Alyssa Cordes, Michael U. J. Oliphant, S. Aidan Quinn, Mayura Thomas, Laura M. Selfors, Francesca Silvestri, Nomeda Girnius, Gianmarco Rinaldi, Jason J. Zoeller, Hana Shapiro, Christina Tsiobikas, Kushali P. Gupta, Shailja Pathania, Aviv Regev, Cigall Kadoch, Senthil K. Muthuswamy, Joan S. Brugge
Germline BRCA1 mutation carriers face a high breast cancer risk; however, the underlying mechanisms for this risk are not completely understood. Using a new genetically engineered mouse model of germline Brca1 heterozygosity, we demonstrate that early tumor onset in a Brca1 heterozygous background cannot be fully explained by the conventional ‘two-hit’ hypothesis, suggesting the existence of inherent tumor-promoting alterations in the Brca1 heterozygous state. Single-cell RNA sequencing and assay for transposase-accessible chromatin with sequencing analyses uncover a unique set of differentially accessible chromatin regions in ostensibly normal Brca1 heterozygous mammary epithelial cells, distinct from wild-type cells and partially mimicking the chromatin and RNA-level changes in tumor cells. Transcription factor analyses identify loss of ELF5 and gain of AP-1 sites in these epigenetically primed regions; in vivo experiments further implicate AP-1 and Wnt10a as strong promoters of Brca1-related breast cancer. These findings reveal a previously unappreciated epigenetic effect of Brca1 haploinsufficiency in accelerating tumorigenesis, advancing our mechanistic understanding and informing potential therapeutic strategies. A second hit to Brca1 in heterozygous mice leads to accelerated tumor development compared to wild-type mice in which both alleles are simultaneously deleted. This is because of an epigenetic state associated with Brca1 haploinsufficiency that impacts AP-1 and Wnt10a.
{"title":"Brca1 haploinsufficiency promotes early tumor onset and epigenetic alterations in a mouse model of hereditary breast cancer","authors":"Carman Man-Chung Li, Alyssa Cordes, Michael U. J. Oliphant, S. Aidan Quinn, Mayura Thomas, Laura M. Selfors, Francesca Silvestri, Nomeda Girnius, Gianmarco Rinaldi, Jason J. Zoeller, Hana Shapiro, Christina Tsiobikas, Kushali P. Gupta, Shailja Pathania, Aviv Regev, Cigall Kadoch, Senthil K. Muthuswamy, Joan S. Brugge","doi":"10.1038/s41588-024-01958-6","DOIUrl":"10.1038/s41588-024-01958-6","url":null,"abstract":"Germline BRCA1 mutation carriers face a high breast cancer risk; however, the underlying mechanisms for this risk are not completely understood. Using a new genetically engineered mouse model of germline Brca1 heterozygosity, we demonstrate that early tumor onset in a Brca1 heterozygous background cannot be fully explained by the conventional ‘two-hit’ hypothesis, suggesting the existence of inherent tumor-promoting alterations in the Brca1 heterozygous state. Single-cell RNA sequencing and assay for transposase-accessible chromatin with sequencing analyses uncover a unique set of differentially accessible chromatin regions in ostensibly normal Brca1 heterozygous mammary epithelial cells, distinct from wild-type cells and partially mimicking the chromatin and RNA-level changes in tumor cells. Transcription factor analyses identify loss of ELF5 and gain of AP-1 sites in these epigenetically primed regions; in vivo experiments further implicate AP-1 and Wnt10a as strong promoters of Brca1-related breast cancer. These findings reveal a previously unappreciated epigenetic effect of Brca1 haploinsufficiency in accelerating tumorigenesis, advancing our mechanistic understanding and informing potential therapeutic strategies. A second hit to Brca1 in heterozygous mice leads to accelerated tumor development compared to wild-type mice in which both alleles are simultaneously deleted. This is because of an epigenetic state associated with Brca1 haploinsufficiency that impacts AP-1 and Wnt10a.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"56 12","pages":"2763-2775"},"PeriodicalIF":31.7,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142598341","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-08DOI: 10.1038/s41588-024-02010-3
Wei Li
{"title":"Multimodal optical pooled screening with CRISPRmap","authors":"Wei Li","doi":"10.1038/s41588-024-02010-3","DOIUrl":"10.1038/s41588-024-02010-3","url":null,"abstract":"","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"56 11","pages":"2296-2296"},"PeriodicalIF":31.7,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142596129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-08DOI: 10.1038/s41588-024-02002-3
The standardized naming of gene variants in both databases and publications is crucial to ensure their discoverability and clinical application. Efforts are underway in conjunction with the Human Genome Organization (HUGO) to develop a field standard for variant reporting through the use of validation software prior to publication.
{"title":"Improving reporting standards for genetic variants","authors":"","doi":"10.1038/s41588-024-02002-3","DOIUrl":"10.1038/s41588-024-02002-3","url":null,"abstract":"The standardized naming of gene variants in both databases and publications is crucial to ensure their discoverability and clinical application. Efforts are underway in conjunction with the Human Genome Organization (HUGO) to develop a field standard for variant reporting through the use of validation software prior to publication.","PeriodicalId":18985,"journal":{"name":"Nature genetics","volume":"56 11","pages":"2283-2283"},"PeriodicalIF":31.7,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41588-024-02002-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142596169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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