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Mathys H, Peng Z, Boix CA, Victor MB, Leary N, Babu S, Abdelhady G, Jiang X, Ng AP, Ghafari K, Kunisky AK, Mantero J, Galani K, Lohia VN, Fortier GE, Lotfi Y, Ivey J, Brown HP, Patel PR, Chakraborty N, Beaudway JI, Imhoff EJ, Keeler CF, McChesney MM, Patel HH, Patel SP, Thai MT, Bennett DA, Kellis M, Tsai LH. Single-cell atlas reveals correlates of high cognitive function, dementia, and resilience to Alzheimer's disease pathology. Cell 2023; 186:4365-4385.e27. [PMID: 37774677 PMCID: PMC10601493 DOI: 10.1016/j.cell.2023.08.039] [Citation(s) in RCA: 32] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 05/20/2023] [Accepted: 08/29/2023] [Indexed: 10/01/2023]
Abstract
Alzheimer's disease (AD) is the most common cause of dementia worldwide, but the molecular and cellular mechanisms underlying cognitive impairment remain poorly understood. To address this, we generated a single-cell transcriptomic atlas of the aged human prefrontal cortex covering 2.3 million cells from postmortem human brain samples of 427 individuals with varying degrees of AD pathology and cognitive impairment. Our analyses identified AD-pathology-associated alterations shared between excitatory neuron subtypes, revealed a coordinated increase of the cohesin complex and DNA damage response factors in excitatory neurons and in oligodendrocytes, and uncovered genes and pathways associated with high cognitive function, dementia, and resilience to AD pathology. Furthermore, we identified selectively vulnerable somatostatin inhibitory neuron subtypes depleted in AD, discovered two distinct groups of inhibitory neurons that were more abundant in individuals with preserved high cognitive function late in life, and uncovered a link between inhibitory neurons and resilience to AD pathology.
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Affiliation(s)
- Hansruedi Mathys
- Picower Institute for Learning and Memory, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA; University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA.
| | - Zhuyu Peng
- Picower Institute for Learning and Memory, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Carles A Boix
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Matheus B Victor
- Picower Institute for Learning and Memory, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Noelle Leary
- Picower Institute for Learning and Memory, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Sudhagar Babu
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Ghada Abdelhady
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Xueqiao Jiang
- Picower Institute for Learning and Memory, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Ayesha P Ng
- Picower Institute for Learning and Memory, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Kimia Ghafari
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Alexander K Kunisky
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Julio Mantero
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Kyriaki Galani
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Vanshika N Lohia
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Gabrielle E Fortier
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Yasmine Lotfi
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Jason Ivey
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Hannah P Brown
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Pratham R Patel
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Nehal Chakraborty
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Jacob I Beaudway
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Elizabeth J Imhoff
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Cameron F Keeler
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Maren M McChesney
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Haishal H Patel
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Sahil P Patel
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | - Megan T Thai
- University of Pittsburgh Brain Institute and Department of Neurobiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA
| | | | - Manolis Kellis
- Computer Science and Artificial Intelligence Laboratory, MIT, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
| | - Li-Huei Tsai
- Picower Institute for Learning and Memory, MIT, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
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Eikelboom JW, Ivey L, Ivey J, Baker RI. Familial thrombophilia and the prothrombin 20210A mutation: association with increased thrombin generation and unusual thrombosis. Blood Coagul Fibrinolysis 1999; 10:1-5. [PMID: 10070829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/11/2023]
Abstract
The 20210A prothrombin mutation has recently been associated with an increased risk of venous thrombosis, but the mechanism of the increased thrombotic risk in affected persons has not been elucidated. We report on a thrombophilic family in which the proband presented with cerebral vein thrombosis and homozygosity for the 20210A prothrombin mutation as her only identifiable risk factor for venous thrombosis. Extended genotyping of family members revealed seven other affected, but asymptomatic, first-degree relatives (one A/A homozygote and six G/A heterozygotes). Plasma levels of prothrombin, prothrombin fragments 1 + 2 and thrombin-antithrombin complexes were highest in A/A homozygotes, intermediate in G/A heterozygotes and lowest in those with the G/G homozygous normal genotype, while D-dimer levels were elevated only in A/A homozygotes. Our results suggest that the 20210A prothrombin mutation is associated with activation of coagulation and increased thrombin generation, not only in patients with a past history of thrombosis but also in otherwise healthy asymptomatic persons. In a similar fashion to the homozygous factor V Leiden mutation, patients with the homozygous 20210A prothrombin mutation could be at highest risk of thrombosis, as suggested by our patient who presented with unusual thrombosis.
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Affiliation(s)
- J W Eikelboom
- McMaster University, HGH-McMaster Clinic, Hamilton, Ontario, Canada
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Abstract
Marfan's syndrome (MFS), a heritable connective tissue disorder, may result in cardiac valvular insufficiency, aortic aneurysm or dissection, dislocated lens, and musculoskeletal abnormalities. During a 20-month period (1994-96), an interdisciplinary health care team at a central Virginia medical center evaluated the histories of 112 persons from 15 different families for the presence of MFS-related traits. Seventy-five had at least one MFS-related trait, and 27 subjects underwent echocardiography to evaluate for aortic root dilatation and valvular lesions. Forty-three patients (57.3%) in the above cohort demonstrated significant cardiovascular lesions, with 20 undergoing cardiac surgery. Thirty-one patients (41.3%) were initially seen with significant ocular lesions, and 38 (50.7%) displayed orthopedic deformities. The health care team developed strategies for long-term management of persons with MFS, including antihypertensive therapy, periodic testing, risk-factor modification, genetic counseling, and surgery for appropriate patients. Proactive, consistent management of MFS families will improve long-term health outcomes for this patient population.
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Affiliation(s)
- D Strider
- Thoracic and Cardiovascular Services, University of Virginia Health Sciences Center, Charlottesville
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Hiraishi H, Terano A, Ota S, Shiga J, Kobayashi T, Harada H, Ishii M, Ivey J, Sugimoto T. Prostaglandin production in cultured gastric mucosal cells: role of cAMP on its modulation. Prostaglandins 1986; 32:259-73. [PMID: 3025933 DOI: 10.1016/0090-6980(86)90130-9] [Citation(s) in RCA: 15] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
The effect of cAMP on prostaglandin production may depend on cell types. To clarify the relationship between PG and cAMP, we examined arachidonate's effects on PG synthesis and intracellular cAMP accumulation in monolayers of rat gastric mucosal cells. These cells produced PGE2, PGI2 and thromboxaneA2 (TXA2) in amounts of 316 +/- 18, 100 +/- 7 and 30 +/- 5 pg per 10(5) cells in 10 min, respectively, in response to 10 microM arachidonic acid (AA). The production of these PG, however, leveled off subsequently. Cells initially exposed to AA responded poorly to a subsequent stimulation by AA. AA simultaneously stimulated intracellular cAMP accumulation; this stimulatory effect on cAMP production was abolished by the pretreatment with indomethacin. Nevertheless, the pretreatments with dibutyryl cAMP (0.1-5 mM) did not alter the amount of subsequent AA-induced PGE2 production. Furthermore, the preincubation with 1mM isobutyl methyl xanthine also failed to affect PGE2 synthesis, while it increased intracellular cAMP accumulation. Our studies suggest AA stimulates intracellular cAMP formation in cultured gastric mucosal cells, linked with conversion of AA to cyclooxygenase metabolites, AA-induced PG production is limited in these cells, and it seems, however, unlikely that intracellular cAMP modulates AA metabolism to PG.
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