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Liu J, Song R, Pan R, Yi W, Jin X, Song J, Cheng J, Zhang X, Su H. Extreme temperatures, PM 2.5 and trajectories of impaired thyroid hormone sensitivity: A longitudinal study of patients with schizophrenia. ENVIRONMENT INTERNATIONAL 2024; 191:108961. [PMID: 39173235 DOI: 10.1016/j.envint.2024.108961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/28/2024] [Revised: 08/14/2024] [Accepted: 08/14/2024] [Indexed: 08/24/2024]
Abstract
BACKGROUND The climate change scenario has witnessed an increase in extreme temperature events (ETEs), including heat waves and cold spells, and a heightened occurrence of compounding with fine particulate matter (PM2.5). However, the impact of this phenomenon on the sensitivity to thyroid hormones (THs) in humans is unclear, especially in a group as specific as schizophrenia. METHODS A longitudinal study was constructed using longitudinal measurements of thyroid function in schizophrenia in the Anhui Mental Health Center. The latent growth mixture model was applied to assess the optimal trajectory of change in impaired THs sensitivity. We then used logistic regression to explore associations between heat waves, cold spells, and PM2.5 with impaired THs sensitivity trajectories in the total population and different gender and age subgroups. Furthermore, the effect of the frequency, intensity, and duration of ETEs in the above associations was explored, as well as an assessment of the interaction between ETEs and PM2.5. RESULTS Among 931 participants, we identified two classifications of trajectories of impaired THs sensitivity: "Low-stable" (n = 836, 89.80 %) and "Rise-slight down" (n = 95, 10.20 %). Logistic regression showed significant associations between each additional day of heat waves (≥3 days with temperature thresholds above the 95th percentile) and cold spells (≥3 days with temperature thresholds below the 5th percentile) and "Rise-slight down" trajectory, with odds ratios (95 % confidence intervals) of 1.06 (1.02, 1.10) and 1.19 (1.14, 1.24), respectively, and the strength of this association increased with the intensity and duration of ETEs. Subgroup analyses indicated that the association was more pronounced in males and the age group above 40 years. Furthermore, PM2.5 was found to interact with heat waves, with high concentrations exacerbating the effects of heat waves. CONCLUSIONS Our findings suggest that mitigating both ETEs and PM2.5 exposures may bring health co-benefits in preventing thyroid impairment in schizophrenia.
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Affiliation(s)
- Jintao Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China; Anhui Mental Health Center (Affiliated Psychological Hospital of Anhui Medical University), Hefei, Anhui, China
| | - Rong Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China; Anhui Mental Health Center (Affiliated Psychological Hospital of Anhui Medical University), Hefei, Anhui, China
| | - Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China; Anhui Mental Health Center (Affiliated Psychological Hospital of Anhui Medical University), Hefei, Anhui, China
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China; Anhui Mental Health Center (Affiliated Psychological Hospital of Anhui Medical University), Hefei, Anhui, China
| | - Xiaoyu Jin
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China; Anhui Mental Health Center (Affiliated Psychological Hospital of Anhui Medical University), Hefei, Anhui, China
| | - Jian Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China; Anhui Mental Health Center (Affiliated Psychological Hospital of Anhui Medical University), Hefei, Anhui, China
| | - Jian Cheng
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China; Anhui Mental Health Center (Affiliated Psychological Hospital of Anhui Medical University), Hefei, Anhui, China
| | - Xulai Zhang
- Anhui Mental Health Center (Affiliated Psychological Hospital of Anhui Medical University), Hefei, Anhui, China.
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui Medical University, Hefei, Anhui, China; Center for Big Data and Population Health of IHM, Hefei, Anhui, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Hefei, Anhui, China; Anhui Mental Health Center (Affiliated Psychological Hospital of Anhui Medical University), Hefei, Anhui, China.
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Wang Y, Su C, Liu Q, Hao X, Han S, Doretto LB, Rosa IF, Yang Y, Shao C, Wang Q. Transcriptome Analysis Revealed the Early Heat Stress Response in the Brain of Chinese Tongue Sole ( Cynoglossus semilaevis). Animals (Basel) 2023; 14:84. [PMID: 38200815 PMCID: PMC10777917 DOI: 10.3390/ani14010084] [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: 10/05/2023] [Revised: 11/24/2023] [Accepted: 11/27/2023] [Indexed: 01/12/2024] Open
Abstract
As a common influencing factor in the environment, temperature greatly influences the fish that live in the water all their life. The essential economic fish Chinese tongue sole (Cynoglossus semilaevis), a benthic fish, will experience both physiological and behavioral changes due to increases in temperature. The brain, as the central hub of fish and a crucial regulatory organ, is particularly sensitive to temperature changes and will be affected. However, previous research has mainly concentrated on the impact of temperature on the gonads of C. semilaevis. Instead, our study examines the brain using transcriptomics to investigate specific genes and pathways that can quickly respond to temperature changes. The fish were subjected to various periods of heat stress (1 h, 2 h, 3 h, and 5 h) before extracting the brain for transcriptome analysis. After conducting transcriptomic analyses, we identified distinct genes and pathways in males and females. The pathways were mainly related to cortisol synthesis and secretion, neuroactive ligand-receptor interactions, TGF beta signaling pathway, and JAK/STAT signaling pathway, while the genes included the HSP family, tshr, c-fos, c-jun, cxcr4, camk2b, and igf2. Our study offers valuable insights into the regulation mechanisms of the brain's response to temperature stress.
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Affiliation(s)
- Yue Wang
- Tianjin Key Laboratory of Aqua-Ecology and Aquaculture, Fisheries College, Tianjin Agricultural University, Tianjin 300384, China; (Y.W.); (Y.Y.)
| | - Chengcheng Su
- National Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, China; (C.S.); (Q.L.); (X.H.); (S.H.); (L.B.D.); (C.S.)
| | - Qian Liu
- National Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, China; (C.S.); (Q.L.); (X.H.); (S.H.); (L.B.D.); (C.S.)
| | - Xiancai Hao
- National Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, China; (C.S.); (Q.L.); (X.H.); (S.H.); (L.B.D.); (C.S.)
| | - Shenglei Han
- National Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, China; (C.S.); (Q.L.); (X.H.); (S.H.); (L.B.D.); (C.S.)
| | - Lucas B. Doretto
- National Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, China; (C.S.); (Q.L.); (X.H.); (S.H.); (L.B.D.); (C.S.)
| | - Ivana F. Rosa
- Department of Structural and Functional Biology, Institute of Biosciences, São Paulo State University (UNESP), Botucatu 01049-010, Brazil;
| | - Yanjing Yang
- Tianjin Key Laboratory of Aqua-Ecology and Aquaculture, Fisheries College, Tianjin Agricultural University, Tianjin 300384, China; (Y.W.); (Y.Y.)
| | - Changwei Shao
- National Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, China; (C.S.); (Q.L.); (X.H.); (S.H.); (L.B.D.); (C.S.)
- Laboratory for Marine Fisheries Science and Food Production Processes, Laoshan Laboratory, Qingdao 266237, China
| | - Qian Wang
- National Key Laboratory of Mariculture Biobreeding and Sustainable Goods, Yellow Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Qingdao 266071, China; (C.S.); (Q.L.); (X.H.); (S.H.); (L.B.D.); (C.S.)
- Laboratory for Marine Fisheries Science and Food Production Processes, Laoshan Laboratory, Qingdao 266237, China
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