Pub Date : 2024-07-27DOI: 10.1101/2024.07.26.24311080
Guihong Wan, Sara Khattab, Katie Roster, Nga Nguyen, Boshen Yan, Hannah Rashdan, Hossein Estiri, Yevgeniy R. Semenov
Background: Melanoma is a lethal form of skin cancer with a high propensity for metastasizing, making early detection crucial. This study aims to develop a machine learning model using electronic health record data to identify patients at high risk of developing melanoma to prioritize them for dermatology screening. Methods: This retrospective study included patients diagnosed with melanoma (cases), as well as matched patients without melanoma (controls), from Massachusetts General Hospital (MGH), Brigham and Women's Hospital (BWH), Dana-Farber Cancer Institute (DFCI), and other hospital centers within the Research Patient Data Registry at Mass General Brigham healthcare system between 1992 and 2022. Patient demographics, family history, diagnoses, medications, procedures, laboratory tests, reasons for visits, and allergy data six months prior to the date of first melanoma diagnosis or date of censoring were extracted. A machine learning framework for health outcomes (MLHO) was utilized to build the model. Performance was evaluated using five-fold cross-validation of the MGH cohort (internal validation) and by using the MGH cohort for model training and the non-MGH cohort for independent testing (external validation). The Area Under the Receiver Operating Characteristic Curve (AUC-ROC) and the Area Under the Precision-Recall Curve (AUC-PR), along with 95% Confidence Intervals (CIs), were computed. Results: This study identified 10,778 patients with melanoma and 10,778 matched patients without melanoma, including 8,944 from MGH and 1,834 from non-MGH hospitals in each cohort, both with an average follow-up duration of 9 years. In the internal and external validations, the model achieved AUC-ROC values of 0.826 (95% CI: 0.819-0.832) and 0.823 (95% CI: 0.809-0.837) and AUC-PR scores of 0.841 (95% CI: 0.834-0.848) and 0.822 (95% CI: 0.806-0.839), respectively. Important risk features included a family history of melanoma, a family history of skin cancer, and a prior diagnosis of benign neoplasm of skin. Conversely, medical examination without abnormal findings was identified as a protective feature. Conclusions: Machine learning techniques and electronic health records can be effectively used to predict melanoma risk, potentially aiding in identifying high-risk patients and enabling individualized screening strategies for melanoma.
{"title":"Individualized melanoma risk prediction using machine learning with electronic health records","authors":"Guihong Wan, Sara Khattab, Katie Roster, Nga Nguyen, Boshen Yan, Hannah Rashdan, Hossein Estiri, Yevgeniy R. Semenov","doi":"10.1101/2024.07.26.24311080","DOIUrl":"https://doi.org/10.1101/2024.07.26.24311080","url":null,"abstract":"Background:\u0000Melanoma is a lethal form of skin cancer with a high propensity for metastasizing, making early detection crucial. This study aims to develop a machine learning model using electronic health record data to identify patients at high risk of developing melanoma to prioritize them for dermatology screening.\u0000Methods:\u0000This retrospective study included patients diagnosed with melanoma (cases), as well as matched patients without melanoma (controls), from Massachusetts General Hospital (MGH), Brigham and Women's Hospital (BWH), Dana-Farber Cancer Institute (DFCI), and other hospital centers within the Research Patient Data Registry at Mass General Brigham healthcare system between 1992 and 2022. Patient demographics, family history, diagnoses, medications, procedures, laboratory tests, reasons for visits, and allergy data six months prior to the date of first melanoma diagnosis or date of censoring were extracted. A machine learning framework for health outcomes (MLHO) was utilized to build the model. Performance was evaluated using five-fold cross-validation of the MGH cohort (internal validation) and by using the MGH cohort for model training and the non-MGH cohort for independent testing (external validation). The Area Under the Receiver Operating Characteristic Curve (AUC-ROC) and the Area Under the Precision-Recall Curve (AUC-PR), along with 95% Confidence Intervals (CIs), were computed. Results:\u0000This study identified 10,778 patients with melanoma and 10,778 matched patients without melanoma, including 8,944 from MGH and 1,834 from non-MGH hospitals in each cohort, both with an average follow-up duration of 9 years. In the internal and external validations, the model achieved AUC-ROC values of 0.826 (95% CI: 0.819-0.832) and 0.823 (95% CI: 0.809-0.837) and AUC-PR scores of 0.841 (95% CI: 0.834-0.848) and 0.822 (95% CI: 0.806-0.839), respectively. Important risk features included a family history of melanoma, a family history of skin cancer, and a prior diagnosis of benign neoplasm of skin. Conversely, medical examination without abnormal findings was identified as a protective feature.\u0000Conclusions:\u0000Machine learning techniques and electronic health records can be effectively used to predict melanoma risk, potentially aiding in identifying high-risk patients and enabling individualized screening strategies for melanoma.","PeriodicalId":501385,"journal":{"name":"medRxiv - Dermatology","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141783247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-24DOI: 10.1101/2024.07.23.24310907
Jun Hu, Jiayan Chen, Peiyan Wang, Changji Xiao, Kalibinuer Kelaimu, Xianshu Gao, Xiaomei Li
(1) Background: Recent studies suggest a potential link between gut microbiomes (GMs) and inflammatory diseases, but the role of GMs in lichen sclerosus (LS) remains unclear. This study aims to investigate the causal relationship between GMs and LS, focusing on key GM taxa. (2) Methods: We utilized GWAS summary statistics for 211 GM taxa and their association with 2,445 LS patients and 353,088 healthy controls, employing Mendelian randomization (MR). GWAS data for GM taxa came from the MiBioGen consortium, and for LS from the FinnGen consortium. The primary analytical tools included the inverse-variance weighted (IVW) method, weighted MR, simple mode, weighted median, and MR-Egger methods. Sensitivity analyses included leave-one-out analysis, MR-Egger intercept test, MR-PRESSO global test, and Cochrane's Q-test. A reverse MR analysis was conducted on bacteria identified in the forward MR study. (3) Results: We identified one strong causal relationship: order Burkholderiales [odds ratio (OR) = 0.420, 95% confidence interval (CI): 0.230 - 0.765, p = 0.005], and three nominally significant relationships: phylum Cyanobacteria (OR = 0.585, 95% CI: 0.373 - 0.919, p = 0.020), class Betaproteobacteria (OR = 0.403, 95% CI: 0.189 - 0.857, p = 0.018), and genus Butyrivibrio (OR = 0.678, 95% CI: 0.507 - 0.907, p = 0.009). Moreover, this MR analysis was not impacted by horizontal pleiotropy, according to the MR-Egger intercept test and MR-PRESSO global test (p > 0.05). Remarkably, the reliability of our results was confirmed by leave-one-out analysis. Reverse MR analysis showed no significant causal relationship between LS and GM. (4) Conclusions: This MR study identifies specific gut flora linked to a lower risk of LS, offering new insights for disease treatment and prevention. Future research should incorporate metagenomics sequencing of extensive microbiome GWAS datasets.
{"title":"Gut microbiome and lichen sclerosus: a two-sample bi-directional Mendelian randomization study","authors":"Jun Hu, Jiayan Chen, Peiyan Wang, Changji Xiao, Kalibinuer Kelaimu, Xianshu Gao, Xiaomei Li","doi":"10.1101/2024.07.23.24310907","DOIUrl":"https://doi.org/10.1101/2024.07.23.24310907","url":null,"abstract":"(1) Background: Recent studies suggest a potential link between gut microbiomes (GMs) and inflammatory diseases, but the role of GMs in lichen sclerosus (LS) remains unclear. This study aims to investigate the causal relationship between GMs and LS, focusing on key GM taxa. (2) Methods: We utilized GWAS summary statistics for 211 GM taxa and their association with 2,445 LS patients and 353,088 healthy controls, employing Mendelian randomization (MR). GWAS data for GM taxa came from the MiBioGen consortium, and for LS from the FinnGen consortium. The primary analytical tools included the inverse-variance weighted (IVW) method, weighted MR, simple mode, weighted median, and MR-Egger methods. Sensitivity analyses included leave-one-out analysis, MR-Egger intercept test, MR-PRESSO global test, and Cochrane's Q-test. A reverse MR analysis was conducted on bacteria identified in the forward MR study. (3) Results: We identified one strong causal relationship: order Burkholderiales [odds ratio (OR) = 0.420, 95% confidence interval (CI): 0.230 - 0.765, p = 0.005], and three nominally significant relationships: phylum Cyanobacteria (OR = 0.585, 95% CI: 0.373 - 0.919, p = 0.020), class Betaproteobacteria (OR = 0.403, 95% CI: 0.189 - 0.857, p = 0.018), and genus Butyrivibrio (OR = 0.678, 95% CI: 0.507 - 0.907, p = 0.009). Moreover, this MR analysis was not impacted by horizontal pleiotropy, according to the MR-Egger intercept test and MR-PRESSO global test (p > 0.05). Remarkably, the reliability of our results was confirmed by leave-one-out analysis. Reverse MR analysis showed no significant causal relationship between LS and GM. (4) Conclusions: This MR study identifies specific gut flora linked to a lower risk of LS, offering new insights for disease treatment and prevention. Future research should incorporate metagenomics sequencing of extensive microbiome GWAS datasets.","PeriodicalId":501385,"journal":{"name":"medRxiv - Dermatology","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141783248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-24DOI: 10.1101/2024.07.24.24310661
Rana El Masri, Alberto Iannuzzo, Paul Kuentz, Rachida Tacine, Marie Vincent, Sebastien Barbarot, Fanny Morice-Picard, Franck Boralevi, Naia Oillarburu, Juliette Mazereeuw-Hautier, Yannis Duffourd, Laurence Faivre, Arthur Sorlin, Pierre Vabres, Jerome Delon
The genetic bases of mosaic pigmentation disorders have increasingly been identified, but these conditions remain poorly characterised, and their pathophysiology is unclear. Here, we report in four unrelated patients that a recurrent postzygotic mutation in GNA13 is responsible for a recognizable syndrome with hypomelanosis of Ito associated with developmental anomalies. GNA13 encodes Galpha13, a subunit of alpha-beta-gamme heterotrimeric G proteins coupled to specific transmembrane receptors known as G-protein coupled receptors. In-depth functional investigations revealed that this R200K mutation provides a gain of function to Galpha13. Mechanistically, we show that this variant hyperactivates the RHOA/ROCK signalling pathway that consequently increases actin polymerisation and myosin light chains phosphorylation, and promotes melanocytes rounding. Our results also indicate that R200K Galpha13 hyperactivates the YAP signalling pathway. All these changes appear to affect cell migration and adhesion but not the proliferation. Our results suggest that hypopigmentation can result from a defect in melanosome transfer to keratinocytes due to cell shape alterations. These findings highlight the interaction between heterotrimeric G proteins and the RHOA pathway, and their role in melanocyte function.
马赛克色素沉着病的遗传基础已被越来越多地发现，但这些病症的特征仍不十分明确，其病理生理学也不清楚。在这里，我们报告了四名无血缘关系的患者，GNA13 的复发性杂交后突变是导致伊藤色素沉着与发育异常的可识别综合征的原因。GNA13 编码 Galpha13，它是α-β-甘氨酸异三聚 G 蛋白的一个亚基，与被称为 G 蛋白偶联受体的特定跨膜受体偶联。深入的功能研究发现，R200K 突变为 Galpha13 提供了功能增益。从机理上讲，我们发现这种变异会过度激活 RHOA/ROCK 信号通路，从而增加肌动蛋白的聚合和肌球蛋白轻链的磷酸化，促进黑色素细胞变圆。我们的研究结果还表明，R200K Galpha13 会过度激活 YAP 信号通路。所有这些变化似乎都会影响细胞迁移和粘附，但不会影响细胞增殖。我们的研究结果表明，色素沉着可能是由于细胞形状改变导致黑色素小体向角质形成细胞转移的缺陷造成的。这些发现突显了异三聚体 G 蛋白与 RHOA 通路之间的相互作用，以及它们在黑色素细胞功能中的作用。
{"title":"A postzygotic GNA13 variant upregulates the RHOA/ROCK pathway and alters melanocyte function in a mosaic skin hypopigmentation syndrome","authors":"Rana El Masri, Alberto Iannuzzo, Paul Kuentz, Rachida Tacine, Marie Vincent, Sebastien Barbarot, Fanny Morice-Picard, Franck Boralevi, Naia Oillarburu, Juliette Mazereeuw-Hautier, Yannis Duffourd, Laurence Faivre, Arthur Sorlin, Pierre Vabres, Jerome Delon","doi":"10.1101/2024.07.24.24310661","DOIUrl":"https://doi.org/10.1101/2024.07.24.24310661","url":null,"abstract":"The genetic bases of mosaic pigmentation disorders have increasingly been identified, but these conditions remain poorly characterised, and their pathophysiology is unclear. Here, we report in four unrelated patients that a recurrent postzygotic mutation in GNA13 is responsible for a recognizable syndrome with hypomelanosis of Ito associated with developmental anomalies. GNA13 encodes Galpha13, a subunit of alpha-beta-gamme heterotrimeric G proteins coupled to specific transmembrane receptors known as G-protein coupled receptors. In-depth functional investigations revealed that this R200K mutation provides a gain of function to Galpha13. Mechanistically, we show that this variant hyperactivates the RHOA/ROCK signalling pathway that consequently increases actin polymerisation and myosin light chains phosphorylation, and promotes melanocytes rounding. Our results also indicate that R200K Galpha13 hyperactivates the YAP signalling pathway. All these changes appear to affect cell migration and adhesion but not the proliferation. Our results suggest that hypopigmentation can result from a defect in melanosome transfer to keratinocytes due to cell shape alterations. These findings highlight the interaction between heterotrimeric G proteins and the RHOA pathway, and their role in melanocyte function.","PeriodicalId":501385,"journal":{"name":"medRxiv - Dermatology","volume":"55 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141786033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-18DOI: 10.1101/2024.07.17.24310584
Lio Yu, Michael Kaczmarski, Clay Cockerell
Background High risk (HR) basal cell carcinoma (BCC) subtypes have been associated with high recurrence rates that is felt to be better managed surgically. Specifically, Mohs Micrographic Surgery (MMS) is considered most effective for aggressive HR BCCs and superior to traditional nonsurgical techniques, including radiation. Recently, superficial radiation therapy with high resolution ultrasound image guidance called Image Guided Superficial Radiation Therapy (IGSRT) displayed high local control (LC) rates and is an emerging non-surgical alternative to MMS for non-melanoma skin cancer (NMSC). Objectives We present the largest experience in the USA on treatment of BCCs using IGSRT and specifically evaluate if there are differences in LC between HR BCC versus non-HR subtypes using this technology. Methods A retrospective analysis was conducted on 7,994 BCC lesions treated with IGSRT in the continental United States. We compared the results of BCCs treated with IGSRT separated by HR vs non HR groups including 339 HR BCC lesions and 7655 non HR BCC lesions. High risk was defined as infiltrative, micronodular, morpheaform, and sclerosing subtypes. Non-HR BCC included superficial, nodular, and not otherwise specified (NOS) subtypes. Local control (LC) rates at two and five years were calculated with actuarial life-table and Kaplan-Meier methods and statistically compared using log rank tests. Results IGSRT treatment of the HR BCC group showed no recurrences with two and five-year actuarial and KM LC rates all at 100%. In comparison, the non-HR BCC cohort achieved similar two and five-year actuarial LC rates of 99.71% and 99.24% (KM LC at 99.5% and 99.23%), respectively. No statistical differences in LC rates between the two cohorts (p=0.278 each) resulted. Patients tolerated treatment well with little or rare high grade RTOG toxicity reported in both cohorts. Conclusion HR BCC may be treated just as effectively as low risk BCC using IGSRT and presents a viable alternative to MMS. The targeted approach using IGSRT, incorporating high resolution dermal ultrasound (HRDUS), appear to enhance treatment accuracy and effectiveness demonstrating high LC rates in all subtypes of BCC comparable to MMS and is a viable non-surgical option.
{"title":"Radiation sensitivity and efficacy in aggressive and non-aggressive basal cell carcinoma (BCC) of the skin: Image Guided Superficial Radiation Therapy achieves high rate of local control in sclerosing, infiltrative, morpheaform and micronodular BCC subtypes as well as in non high risk BCCs, an analysis of 7994 BCC lesions.","authors":"Lio Yu, Michael Kaczmarski, Clay Cockerell","doi":"10.1101/2024.07.17.24310584","DOIUrl":"https://doi.org/10.1101/2024.07.17.24310584","url":null,"abstract":"Background High risk (HR) basal cell carcinoma (BCC) subtypes have been associated with high recurrence rates that is felt to be better managed surgically. Specifically, Mohs Micrographic Surgery (MMS) is considered most effective for aggressive HR BCCs and superior to traditional nonsurgical techniques, including radiation. Recently, superficial radiation therapy with high resolution ultrasound image guidance called Image Guided Superficial Radiation Therapy (IGSRT) displayed high local control (LC) rates and is an emerging non-surgical alternative to MMS for non-melanoma skin cancer (NMSC). Objectives We present the largest experience in the USA on treatment of BCCs using IGSRT and specifically evaluate if there are differences in LC between HR BCC versus non-HR subtypes using this technology. Methods A retrospective analysis was conducted on 7,994 BCC lesions treated with IGSRT in the continental United States. We compared the results of BCCs treated with IGSRT separated by HR vs non HR groups including 339 HR BCC lesions and 7655 non HR BCC lesions. High risk was defined as infiltrative, micronodular, morpheaform, and sclerosing subtypes. Non-HR BCC included superficial, nodular, and not otherwise specified (NOS) subtypes. Local control (LC) rates at two and five years were calculated with actuarial life-table and Kaplan-Meier methods and statistically compared using log rank tests. Results IGSRT treatment of the HR BCC group showed no recurrences with two and five-year actuarial and KM LC rates all at 100%. In comparison, the non-HR BCC cohort achieved similar two and five-year actuarial LC rates of 99.71% and 99.24% (KM LC at 99.5% and 99.23%), respectively. No statistical differences in LC rates between the two cohorts (p=0.278 each) resulted. Patients tolerated treatment well with little or rare high grade RTOG toxicity reported in both cohorts. Conclusion HR BCC may be treated just as effectively as low risk BCC using IGSRT and presents a viable alternative to MMS. The targeted approach using IGSRT, incorporating high resolution dermal ultrasound (HRDUS), appear to enhance treatment accuracy and effectiveness demonstrating high LC rates in all subtypes of BCC comparable to MMS and is a viable non-surgical option.","PeriodicalId":501385,"journal":{"name":"medRxiv - Dermatology","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141745290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-14DOI: 10.1101/2024.07.13.24310236
Shruti Chopra, Lennart M. Roesner, Katinka Döhner, Jana Zeitvogel, Stephan Traidl, Elke Rodriguez, Inken Harder, Lieb Wolfgang, Stephan Weidinger, Thomas F. Schulz, Beate Sodeik, Thomas Werfel
Abstract Background: A subgroup of atopic dermatitis (AD) patients is prone to develop severe, disseminated cutaneous infection with herpes simplex virus (HSV), known as eczema herpeticum (EH). The occurrence of EH in a subset of AD patients and its frequent recurrence implies the importance of genetic factors in its pathogenesis. Objective: We aimed to identify novel genetic risk factors for EH and study their impact on HSV-1 infection. Methods: We performed whole exome sequencing on nine AD patients with (ADEH+) and without (ADEH-) a history of EH in comparison to healthy controls. We validated the finding of a variant of COL23A1 gene (encoding Collagen type XXIII alpha 1 chain) in ADEH in a larger cohort of 117 ADEH+, 117 ADEH- patients and 118 healthy controls by PCR. We studied the expression of COL23A1 in keratinocytes from ADEH+ and ADEH- patients, and the upregulated COL23A1 expression in primary keratinocytes and in the cell line HaCaT to study its role in HSV-1 infection. Results: We identified a single nucleotide polymorphism (SNP), rs2973744 in COL23A1, as a risk factor for EH observed in 5% of ADEH+ patients, 1.6% of healthy donors and 0% of ADEH- patients. Primary human keratinocytes from an ADEH+ patient with SNP rs2973744 expressed higher COL23A1 levels and were more susceptible to HSV-1 than keratinocytes from ADEH- patients. In functional assays we showed that HSV-1 gene expression and cell-to-cell spread was more efficient in keratinocytes with increased expression of COL23A1. Moreover, COL23A1 overexpression in HaCaT cells resulted in transcriptional downregulation of several genes that are involved in an effective immune response (IL1R1, IL32, TLR4, CFH, C3, S100A9, IRF1, and ADAM23) and a notable upregulation of TNC and SPINK5 that are associated with AD. Conclusion: Upregulation of COL23A1 promotes HSV-1 infection presumably by attenuating antiviral responses of keratinocytes. Among other markers, the COL23A1 SNP rs2973744 could be included in the screening of AD patients to identify patients at risk of EH, thus allowing early initiation of therapy.
{"title":"Identification and characterization of collagen XXIII alpha 1 as a novel risk factor for eczema herpeticum","authors":"Shruti Chopra, Lennart M. Roesner, Katinka Döhner, Jana Zeitvogel, Stephan Traidl, Elke Rodriguez, Inken Harder, Lieb Wolfgang, Stephan Weidinger, Thomas F. Schulz, Beate Sodeik, Thomas Werfel","doi":"10.1101/2024.07.13.24310236","DOIUrl":"https://doi.org/10.1101/2024.07.13.24310236","url":null,"abstract":"Abstract Background:\u0000A subgroup of atopic dermatitis (AD) patients is prone to develop severe, disseminated cutaneous infection with herpes simplex virus (HSV), known as eczema herpeticum (EH). The occurrence of EH in a subset of AD patients and its frequent recurrence implies the importance of genetic factors in its pathogenesis. Objective:\u0000We aimed to identify novel genetic risk factors for EH and study their impact on HSV-1 infection. Methods:\u0000We performed whole exome sequencing on nine AD patients with (ADEH+) and without (ADEH-) a history of EH in comparison to healthy controls. We validated the finding of a variant of COL23A1 gene (encoding Collagen type XXIII alpha 1 chain) in ADEH in a larger cohort of 117 ADEH+, 117 ADEH- patients and 118 healthy controls by PCR. We studied the expression of COL23A1 in keratinocytes from ADEH+ and ADEH- patients, and the upregulated COL23A1 expression in primary keratinocytes and in the cell line HaCaT to study its role in HSV-1 infection. Results:\u0000We identified a single nucleotide polymorphism (SNP), rs2973744 in COL23A1, as a risk factor for EH observed in 5% of ADEH+ patients, 1.6% of healthy donors and 0% of ADEH- patients. Primary human keratinocytes from an ADEH+ patient with SNP rs2973744 expressed higher COL23A1 levels and were more susceptible to HSV-1 than keratinocytes from ADEH- patients. In functional assays we showed that HSV-1 gene expression and cell-to-cell spread was more efficient in keratinocytes with increased expression of COL23A1. Moreover, COL23A1 overexpression in HaCaT cells resulted in transcriptional downregulation of several genes that are involved in an effective immune response (IL1R1, IL32, TLR4, CFH, C3, S100A9, IRF1, and ADAM23) and a notable upregulation of TNC and SPINK5 that are associated with AD. Conclusion:\u0000Upregulation of COL23A1 promotes HSV-1 infection presumably by attenuating antiviral responses of keratinocytes. Among other markers, the COL23A1 SNP rs2973744 could be included in the screening of AD patients to identify patients at risk of EH, thus allowing early initiation of therapy.","PeriodicalId":501385,"journal":{"name":"medRxiv - Dermatology","volume":"37 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141719370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Psoriasis is a multifactorial immune-mediated inflammatory disease. Its pathogenesis involves abnormal accumulation of neutrophils and T-cell related abnormalities. Pyroptosis is a type of regulated cell death associated with innate immunity, but its role in psoriasis is unclear. In this study, we found that gasdermin D (Gsdmd) is higher in human psoriatic skin than that in normal skin, and in imiquimod-induced psoriasis-like mouse skin, the expression of Gsdmd was most significantly altered in neutrophils and Il1b was also mainly expressed in neutrophils. Immunohistochemical staining of serial sections of skin lesions from psoriasis patients and healthy control also showed that GSDMD expression is higher in psoriasis lesion, especially in neutrophils. Gsdmd deficiency mitigates psoriasis-like inflammation in mice. GSDMD in neutrophils contributes to psoriasis-like inflammation, while Gsdmd depletion in neutrophils attenuates the development of skin inflammation in psoriasis and reduces the release of the inflammatory cytokines. We found that neutrophil pyroptosis is involved in and contributes to psoriasis inflammation, which provides new insights into the treatment of psoriasis by targeting neutrophil pyroptosis.
{"title":"Gasdermin D-Mediated Neutrophil Pyroptosis drives Inflammation in Psoriasis","authors":"Jian Liu, YuYing Jiang, ZiYue Diao, DanDan Chen, RuiYuan Xia, BingWei Wang, Shuo Yang, ZhiQiang Yin","doi":"10.1101/2024.07.10.24310231","DOIUrl":"https://doi.org/10.1101/2024.07.10.24310231","url":null,"abstract":"Psoriasis is a multifactorial immune-mediated inflammatory disease. Its pathogenesis involves abnormal accumulation of neutrophils and T-cell related abnormalities. Pyroptosis is a type of regulated cell death associated with innate immunity, but its role in psoriasis is unclear. In this study, we found that<em> gasdermin</em><em> D</em><em> (Gsdmd)</em> is higher in human psoriatic skin than that in normal skin, and in imiquimod-induced psoriasis-like mouse skin, the expression of <em>Gsdmd</em> was most significantly altered in neutrophils and <em>Il1b</em> was also mainly expressed in neutrophils. Immunohistochemical staining of serial sections of skin lesions from psoriasis patients and healthy control also showed that GSDMD expression is higher in psoriasis lesion, especially in neutrophils. <em>Gsdmd</em> deficiency mitigates psoriasis-like inflammation in mice. GSDMD in neutrophils contributes to psoriasis-like inflammation, while <em>Gsdmd</em> depletion in neutrophils attenuates the development of skin inflammation in psoriasis and reduces the release of the inflammatory cytokines. We found that neutrophil pyroptosis is involved in and contributes to psoriasis inflammation, which provides new insights into the treatment of psoriasis by targeting neutrophil pyroptosis.","PeriodicalId":501385,"journal":{"name":"medRxiv - Dermatology","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141612645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-03DOI: 10.1101/2024.07.01.24309489
Marita Jenssen, Nikhil Arora, Mari Loset, Bjorn Olav Asvold, Laurent Thomas, Ole-Jorgen Gangso Bekkevold, Xiao-Mei Mai, Yi-Qian Sun, Anne-Sofie Furberg, Rolf Jorde, Tom Wilsgaard, Kjersti Danielsen, Ben M Brumpton
Background: Mendelian randomisation (MR) studies show that higher body mass index (BMI) and lower 25-hydroxyvitamin D (25[OH]D) increase psoriasis risk. The combined effect of these factors has not been explored using factorial MR. Methods: Using cross-sectional data from UK Biobank (UKB, n=398 404) and the Troendelag Health Study (HUNT, n=86 648), we calculated polygenic risk scores for BMI and 25(OH)D to estimate odds ratios for psoriasis using 2x2 and continuous factorial MR. We quantified additive interaction by relative excess risk due to interaction (RERI)-estimates. We also performed traditional observational analyses in UKB. Results: There were 12 207 (3.1%) participants with psoriasis in UKB and 7794 (9.0%) in HUNT. In 2x2 factorial MR, we found no evidence of relative excess risk for psoriasis due to interaction between genetically predicted higher BMI and lower 25(OH)D, neither in UKB (RERI -0.01, 95% confidence interval (CI) -0.08, 0.07) nor in HUNT (RERI -0.04, 95% CI -0.14, 0.06). The same was observed in the continuous factorial MR and observational analyses. Conclusions: This study did not find evidence of interaction between BMI and 25(OH)D on the risk of psoriasis. Given minor differences in measured BMI and 25(OH)D between groups, small effects may have been undetected.
{"title":"Exploring Interaction Between Genetically Predicted Body Mass Index and Serum 25-hydroxyvitamin D Levels on the Odds for Psoriasis in UK Biobank and the HUNT Study: A Factorial Mendelian Randomisation Study","authors":"Marita Jenssen, Nikhil Arora, Mari Loset, Bjorn Olav Asvold, Laurent Thomas, Ole-Jorgen Gangso Bekkevold, Xiao-Mei Mai, Yi-Qian Sun, Anne-Sofie Furberg, Rolf Jorde, Tom Wilsgaard, Kjersti Danielsen, Ben M Brumpton","doi":"10.1101/2024.07.01.24309489","DOIUrl":"https://doi.org/10.1101/2024.07.01.24309489","url":null,"abstract":"Background: Mendelian randomisation (MR) studies show that higher body mass index (BMI) and lower 25-hydroxyvitamin D (25[OH]D) increase psoriasis risk. The combined effect of these factors has not been explored using factorial MR.\u0000Methods: Using cross-sectional data from UK Biobank (UKB, n=398 404) and the Troendelag Health Study (HUNT, n=86 648), we calculated polygenic risk scores for BMI and 25(OH)D to estimate odds ratios for psoriasis using 2x2 and continuous factorial MR. We quantified additive interaction by relative excess risk due to interaction (RERI)-estimates. We also performed traditional observational analyses in UKB. Results: There were 12 207 (3.1%) participants with psoriasis in UKB and 7794 (9.0%) in HUNT. In 2x2 factorial MR, we found no evidence of relative excess risk for psoriasis due to interaction between genetically predicted higher BMI and lower 25(OH)D, neither in UKB (RERI -0.01, 95% confidence interval (CI) -0.08, 0.07) nor in HUNT (RERI -0.04, 95% CI -0.14, 0.06). The same was observed in the continuous factorial MR and observational analyses.\u0000Conclusions: This study did not find evidence of interaction between BMI and 25(OH)D on the risk of psoriasis. Given minor differences in measured BMI and 25(OH)D between groups, small effects may have been undetected.","PeriodicalId":501385,"journal":{"name":"medRxiv - Dermatology","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141547314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-28DOI: 10.1101/2024.06.27.24309562
Albert S Chiou, Jesutofunmi A Omiye, Haiwen Gui, Susan M Swetter, Justin M Ko, Brian Gastman, Joshua Arbesman, Zhou Ran Cai, Olivier Gevaert, Chris Sadee, Veronica M Rotemberg, Seung Seog Han, Philipp Tschandl, Meghan Dickman, Elizabeth Bailey, Gordon H Bae, Philip Bailin, Jennifer Boldrick, Kiana Yekrang, Peter Caroline, Jackson Hanna, Nicholas R Kurtansky, Jochen Weber, Niki A See, Michelle Phung, Marianna Gallegos, Roxana Daneshjou, Roberto Novoa
With an estimated 3 billion people globally lacking access to dermatological care, technological solutions leveraging artificial intelligence (AI) have been proposed to improve access. Diagnostic AI algorithms, however, require high-quality datasets to allow development and testing, particularly those that enable evaluation of both unimodal and multimodal approaches. Currently, the majority of dermatology AI algorithms are built and tested on proprietary, siloed data, often from a single site and with only a single image type (i.e., clinical or dermoscopic). To address this, we developed and released the Melanoma Research Alliance Multimodal Image Dataset for AI-based Skin Cancer (MIDAS) dataset, the largest publicly available, prospectively-recruited, paired dermoscopic- and clinical image-based dataset of biopsy-proven and dermatopathology-labeled skin lesions. We explored model performance on real-world cases using four previously published state-of-the-art (SOTA) models and compared model-to-clinician diagnostic performance. We also assessed algorithm performance using clinical photography taken at different distances from the lesion to assess its influence across diagnostic categories. We prospectively enrolled 796 patients through an IRB-approved protocol with informed consent representing 1290 unique lesions and 3830 total images (including dermoscopic and clinical images taken at 15-cm and 30-cm distance). Images represented the diagnostic diversity of lesions seen in general dermatology, with malignant, benign, and inflammatory lesions that included melanocytic nevi (22%; n=234), invasive cutaneous melanomas (4%; n=46), and melanoma in situ (4%; n=47). When evaluating SOTA models using the MIDAS dataset, we observed performance reduction across all models compared to their previously published performance metrics, indicating challenges to generalizability of current SOTA algorithms. As a comparative baseline, the dermatologists performing biopsies were 79% accurate with their top-1 diagnosis at differentiating a malignant from benign lesion. For malignant lesions, algorithms performed better on images acquired at 15-cm compared to 30-cm distance while dermoscopic images yielded higher sensitivity compared to clinical images. Improving our understanding of the strengths and weaknesses of AI diagnostic algorithms is critical as these tools advance towards widespread clinical deployment. While many algorithms may report high performance metrics, caution should be taken due to the potential for overfitting to localized datasets. MIDAS's robust, multimodal, and diverse dataset allows researchers to evaluate algorithms on our real-world images and better assess their generalizability.
{"title":"Multimodal Image Dataset for AI-based Skin Cancer (MIDAS) Benchmarking","authors":"Albert S Chiou, Jesutofunmi A Omiye, Haiwen Gui, Susan M Swetter, Justin M Ko, Brian Gastman, Joshua Arbesman, Zhou Ran Cai, Olivier Gevaert, Chris Sadee, Veronica M Rotemberg, Seung Seog Han, Philipp Tschandl, Meghan Dickman, Elizabeth Bailey, Gordon H Bae, Philip Bailin, Jennifer Boldrick, Kiana Yekrang, Peter Caroline, Jackson Hanna, Nicholas R Kurtansky, Jochen Weber, Niki A See, Michelle Phung, Marianna Gallegos, Roxana Daneshjou, Roberto Novoa","doi":"10.1101/2024.06.27.24309562","DOIUrl":"https://doi.org/10.1101/2024.06.27.24309562","url":null,"abstract":"With an estimated 3 billion people globally lacking access to dermatological care, technological solutions leveraging artificial intelligence (AI) have been proposed to improve access. Diagnostic AI algorithms, however, require high-quality datasets to allow development and testing, particularly those that enable evaluation of both unimodal and multimodal approaches. Currently, the majority of dermatology AI algorithms are built and tested on proprietary, siloed data, often from a single site and with only a single image type (i.e., clinical or dermoscopic). To address this, we developed and released the Melanoma Research Alliance Multimodal Image Dataset for AI-based Skin Cancer (MIDAS) dataset, the largest publicly available, prospectively-recruited, paired dermoscopic- and clinical image-based dataset of biopsy-proven and dermatopathology-labeled skin lesions. We explored model performance on real-world cases using four previously published state-of-the-art (SOTA) models and compared model-to-clinician diagnostic performance. We also assessed algorithm performance using clinical photography taken at different distances from the lesion to assess its influence across diagnostic categories. We prospectively enrolled 796 patients through an IRB-approved protocol with informed consent representing 1290 unique lesions and 3830 total images (including dermoscopic and clinical images taken at 15-cm and 30-cm distance). Images represented the diagnostic diversity of lesions seen in general dermatology, with malignant, benign, and inflammatory lesions that included melanocytic nevi (22%; n=234), invasive cutaneous melanomas (4%; n=46), and melanoma in situ (4%; n=47). When evaluating SOTA models using the MIDAS dataset, we observed performance reduction across all models compared to their previously published performance metrics, indicating challenges to generalizability of current SOTA algorithms. As a comparative baseline, the dermatologists performing biopsies were 79% accurate with their top-1 diagnosis at differentiating a malignant from benign lesion. For malignant lesions, algorithms performed better on images acquired at 15-cm compared to 30-cm distance while dermoscopic images yielded higher sensitivity compared to clinical images. Improving our understanding of the strengths and weaknesses of AI diagnostic algorithms is critical as these tools advance towards widespread clinical deployment. While many algorithms may report high performance metrics, caution should be taken due to the potential for overfitting to localized datasets. MIDAS's robust, multimodal, and diverse dataset allows researchers to evaluate algorithms on our real-world images and better assess their generalizability.","PeriodicalId":501385,"journal":{"name":"medRxiv - Dermatology","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141505162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background Although exposure to solar radiation is beneficial for humans, too much of it can cause severe health conditions, including sunburn and skin cancer. The biological effects of solar radiation vary enormously with wavelength and exposure time. Ultraviolet and infrared radiations are the two main invisible components of solar radiation, causing skin damage. People are becoming more aware of the significance of sun protection, though little attention is directed to the exposure of the skin to UV and IR radiations through car windows. According to a survey of 1293 participants, mainly from Saudi Arabia, the fact that UV radiation can penetrate through car windows is known by the majority, i.e., 82%. However, the capability of IR radiation to penetrate vehicle windows is unknown to most people. Even though car windows reduce the transmission of ultraviolet and infrared rays, drivers are not isolated from them completely. To the best of our knowledge, this is the first study that measures solar exposure in cars in the middle east region, which is famous for its hot and arid (dry) climate with temperatures reaching over 52°C. Specifically, this study aimed to determine the driver exposure to UV and IR radiations in Dammam, Saudi Arabia, and emphasize the need to take the necessary measures to avoid exposure to these rays.
{"title":"Assessment of Ultraviolet and Infrared Radiations Transmission in Automobile Windshields and Side Windows","authors":"Nouf Jubran AlQahtani, Ghada Naje AlEssa, Hoor Fayez AlDushaishi, Amnah Nabil Bukair, Syed Mehmood Ali","doi":"10.1101/2024.05.27.24307977","DOIUrl":"https://doi.org/10.1101/2024.05.27.24307977","url":null,"abstract":"<strong>Background</strong> Although exposure to solar radiation is beneficial for humans, too much of it can cause severe health conditions, including sunburn and skin cancer. The biological effects of solar radiation vary enormously with wavelength and exposure time. Ultraviolet and infrared radiations are the two main invisible components of solar radiation, causing skin damage. People are becoming more aware of the significance of sun protection, though little attention is directed to the exposure of the skin to UV and IR radiations through car windows. According to a survey of 1293 participants, mainly from Saudi Arabia, the fact that UV radiation can penetrate through car windows is known by the majority, i.e., 82%. However, the capability of IR radiation to penetrate vehicle windows is unknown to most people. Even though car windows reduce the transmission of ultraviolet and infrared rays, drivers are not isolated from them completely. To the best of our knowledge, this is the first study that measures solar exposure in cars in the middle east region, which is famous for its hot and arid (dry) climate with temperatures reaching over 52°C. Specifically, this study aimed to determine the driver exposure to UV and IR radiations in Dammam, Saudi Arabia, and emphasize the need to take the necessary measures to avoid exposure to these rays.","PeriodicalId":501385,"journal":{"name":"medRxiv - Dermatology","volume":"44 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141189333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This research presents a comprehensive usability evaluation of Pathpoint® eDerma Software, conducted in accordance with IEC 62366-1:2015 standards. The study encompasses four diverse user groups, that includes administrators, medical photographers, dermatologists, and patients, ensuring a holistic assessment of the software’s usability and effectiveness. Through a combination of quantitative metrics and qualitative feedback, the study explores various aspects such as accessibility, navigation, safety, and user satisfaction. Potential risks to user experience and patient data security are identified and addressed to ensure compliance with safety standards. The findings highlight the software’s effectiveness in facilitating remote assessments, streamlining workflows, and improving patient care. This research contributes valuable insights to the ongoing refinement and optimisation of eDerma Software, aiming to enhance its usability, safety, and overall effectiveness in real-world healthcare settings.
{"title":"Enhancing Healthcare Accessibility: A Comprehensive Usability Study of Pathpoint® eDerma Software","authors":"Balamurugan Subramaniyan, Atlas Naqvi, Muna Mohamud, Piyush Mahapatra","doi":"10.1101/2024.05.17.24307401","DOIUrl":"https://doi.org/10.1101/2024.05.17.24307401","url":null,"abstract":"This research presents a comprehensive usability evaluation of Pathpoint® eDerma Software, conducted in accordance with IEC 62366-1:2015 standards. The study encompasses four diverse user groups, that includes administrators, medical photographers, dermatologists, and patients, ensuring a holistic assessment of the software’s usability and effectiveness. Through a combination of quantitative metrics and qualitative feedback, the study explores various aspects such as accessibility, navigation, safety, and user satisfaction. Potential risks to user experience and patient data security are identified and addressed to ensure compliance with safety standards. The findings highlight the software’s effectiveness in facilitating remote assessments, streamlining workflows, and improving patient care. This research contributes valuable insights to the ongoing refinement and optimisation of eDerma Software, aiming to enhance its usability, safety, and overall effectiveness in real-world healthcare settings.","PeriodicalId":501385,"journal":{"name":"medRxiv - Dermatology","volume":"220 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141152149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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