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1
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Nathoo N, Neyal N, Kantarci OH, Zeydan B. Imaging phenotypic differences in multiple sclerosis: at the crossroads of aging, sex, race, and ethnicity. Front Glob Womens Health 2024; 5:1412482. [PMID: 39006184 PMCID: PMC11245741 DOI: 10.3389/fgwh.2024.1412482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2024] [Accepted: 06/11/2024] [Indexed: 07/16/2024] Open
Abstract
Clear sex differences are observed in clinical and imaging phenotypes of multiple sclerosis (MS), which evolve significantly over the age spectrum, and more specifically, during reproductive milestones such as pregnancy and menopause. With neuroimaging being an outcome measure and also a key subclinical biomarker of subsequent clinical phenotype in MS, this comprehensive review aims to provide an overview of sex and hormone differences in structural and functional imaging biomarkers of MS, including lesion burden and location, atrophy, white matter integrity, functional connectivity, and iron distribution. Furthermore, how therapies aimed at altering sex hormones can impact imaging of women and men with MS over the lifespan is discussed. This review also explores the key intersection between age, sex, and race/ethnicity in MS, and how this intersection may affect imaging biomarkers of MS.
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Affiliation(s)
- Nabeela Nathoo
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
- Center for Multiple Sclerosis and Autoimmune Neurology, Mayo Clinic, Rochester, MN, United States
| | - Nur Neyal
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
- Center for Multiple Sclerosis and Autoimmune Neurology, Mayo Clinic, Rochester, MN, United States
- Department of Radiology, Mayo Clinic, Rochester, MN, United States
| | - Orhun H Kantarci
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
- Center for Multiple Sclerosis and Autoimmune Neurology, Mayo Clinic, Rochester, MN, United States
| | - Burcu Zeydan
- Department of Neurology, Mayo Clinic, Rochester, MN, United States
- Center for Multiple Sclerosis and Autoimmune Neurology, Mayo Clinic, Rochester, MN, United States
- Department of Radiology, Mayo Clinic, Rochester, MN, United States
- Women's Health Research Center, Mayo Clinic, Rochester, MN, United States
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2
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Zamecnik CR, Sowa GM, Abdelhak A, Dandekar R, Bair RD, Wade KJ, Bartley CM, Kizer K, Augusto DG, Tubati A, Gomez R, Fouassier C, Gerungan C, Caspar CM, Alexander J, Wapniarski AE, Loudermilk RP, Eggers EL, Zorn KC, Ananth K, Jabassini N, Mann SA, Ragan NR, Santaniello A, Henry RG, Baranzini SE, Zamvil SS, Sabatino JJ, Bove RM, Guo CY, Gelfand JM, Cuneo R, von Büdingen HC, Oksenberg JR, Cree BAC, Hollenbach JA, Green AJ, Hauser SL, Wallin MT, DeRisi JL, Wilson MR. An autoantibody signature predictive for multiple sclerosis. Nat Med 2024; 30:1300-1308. [PMID: 38641750 DOI: 10.1038/s41591-024-02938-3] [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: 04/18/2023] [Accepted: 03/21/2024] [Indexed: 04/21/2024]
Abstract
Although B cells are implicated in multiple sclerosis (MS) pathophysiology, a predictive or diagnostic autoantibody remains elusive. In this study, the Department of Defense Serum Repository (DoDSR), a cohort of over 10 million individuals, was used to generate whole-proteome autoantibody profiles of hundreds of patients with MS (PwMS) years before and subsequently after MS onset. This analysis defines a unique cluster in approximately 10% of PwMS who share an autoantibody signature against a common motif that has similarity with many human pathogens. These patients exhibit antibody reactivity years before developing MS symptoms and have higher levels of serum neurofilament light (sNfL) compared to other PwMS. Furthermore, this profile is preserved over time, providing molecular evidence for an immunologically active preclinical period years before clinical onset. This autoantibody reactivity was validated in samples from a separate incident MS cohort in both cerebrospinal fluid and serum, where it is highly specific for patients eventually diagnosed with MS. This signature is a starting point for further immunological characterization of this MS patient subset and may be clinically useful as an antigen-specific biomarker for high-risk patients with clinically or radiologically isolated neuroinflammatory syndromes.
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Affiliation(s)
- Colin R Zamecnik
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Gavin M Sowa
- University of California, San Francisco School of Medicine, San Francisco, CA, USA
- Department of Medicine, McGaw Medical Center of Northwestern University, Chicago, IL, USA
| | - Ahmed Abdelhak
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Ravi Dandekar
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Rebecca D Bair
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Kristen J Wade
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Christopher M Bartley
- Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Kerry Kizer
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Danillo G Augusto
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
- Department of Biological Sciences, University of North Carolina at Charlotte, Charlotte, NC, USA
| | - Asritha Tubati
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Refujia Gomez
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Camille Fouassier
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Chloe Gerungan
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Colette M Caspar
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Jessica Alexander
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Anne E Wapniarski
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Rita P Loudermilk
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Erica L Eggers
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Kelsey C Zorn
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, USA
| | - Kirtana Ananth
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Nora Jabassini
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Sabrina A Mann
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, USA
- Chan Zuckerberg Biohub San Francisco, San Francisco, CA, USA
| | - Nicholas R Ragan
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Adam Santaniello
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Roland G Henry
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Sergio E Baranzini
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Scott S Zamvil
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Joseph J Sabatino
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Riley M Bove
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Chu-Yueh Guo
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Jeffrey M Gelfand
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Richard Cuneo
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - H-Christian von Büdingen
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Jorge R Oksenberg
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Bruce A C Cree
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Jill A Hollenbach
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Ari J Green
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Stephen L Hauser
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Mitchell T Wallin
- Department of Veterans Affairs, Multiple Sclerosis Center of Excellence, Washington, DC, USA
- University of Maryland School of Medicine, Baltimore, MD, USA
| | - Joseph L DeRisi
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, USA
- Chan Zuckerberg Biohub San Francisco, San Francisco, CA, USA
| | - Michael R Wilson
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.
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Williams MJ, Orlando C, Akisanya J, Amezcua L. Multiple Sclerosis in Black and Hispanic Populations: Serving the Underserved. Neurol Clin 2024; 42:295-317. [PMID: 37980120 DOI: 10.1016/j.ncl.2023.06.005] [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: 11/20/2023]
Abstract
Multiple sclerosis has historically been characterized as a disease that affects young women of European ancestry, but recent studies indicate that the incidence and prevalence of the disease is much higher in Black and Hispanic populations than previously recognized. There is evidence that there is a more severe disease course in these populations. , but the intersection of genetic underpinnings and social determinants of health (SDOH) is poorly understood due to the lack of diversity in clinical research. Improving health disparities will involve multiple stakeholders in efforts to improve SDOH and raise awareness about research involvement and the importance of developing personalized health care plans to combat this disease.
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Affiliation(s)
- Mitzi J Williams
- Joi Life Wellness Multiple Sclerosis Center, 767 Concord Road, SE, Smyrna, GA 30082, USA.
| | - Christopher Orlando
- Department of Neurology, University of Southern California, Keck School of Medicine, 1520 San Pablo Street, Suite 3000, Los Angeles, CA, USA. https://twitter.com/OrlandoMDMPH
| | - Jemima Akisanya
- Georgetown Department of Neurology, 10401 Hospital Drive, Suite 102, Clinton, MD 20735, USA. https://twitter.com/MimasMyelin
| | - Lilyana Amezcua
- Department of Neurology, University of Southern California, Keck School of Medicine, 1520 San Pablo Street, Suite 3000, Los Angeles, CA, USA
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4
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Zamecnik CR, Sowa GM, Abdelhak A, Dandekar R, Bair RD, Wade KJ, Bartley CM, Tubati A, Gomez R, Fouassier C, Gerungan C, Alexander J, Wapniarski AE, Loudermilk RP, Eggers EL, Zorn KC, Ananth K, Jabassini N, Mann SA, Ragan NR, Santaniello A, Henry RG, Baranzini SE, Zamvil SS, Bove RM, Guo CY, Gelfand JM, Cuneo R, von Büdingen HC, Oksenberg JR, Cree BAC, Hollenbach JA, Green AJ, Hauser SL, Wallin MT, DeRisi JL, Wilson MR. A Predictive Autoantibody Signature in Multiple Sclerosis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.05.01.23288943. [PMID: 37205595 PMCID: PMC10187343 DOI: 10.1101/2023.05.01.23288943] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Although B cells are implicated in multiple sclerosis (MS) pathophysiology, a predictive or diagnostic autoantibody remains elusive. Here, the Department of Defense Serum Repository (DoDSR), a cohort of over 10 million individuals, was used to generate whole-proteome autoantibody profiles of hundreds of patients with MS (PwMS) years before and subsequently after MS onset. This analysis defines a unique cluster of PwMS that share an autoantibody signature against a common motif that has similarity with many human pathogens. These patients exhibit antibody reactivity years before developing MS symptoms and have higher levels of serum neurofilament light (sNfL) compared to other PwMS. Furthermore, this profile is preserved over time, providing molecular evidence for an immunologically active prodromal period years before clinical onset. This autoantibody reactivity was validated in samples from a separate incident MS cohort in both cerebrospinal fluid (CSF) and serum, where it is highly specific for patients eventually diagnosed with MS. This signature is a starting point for further immunological characterization of this MS patient subset and may be clinically useful as an antigen-specific biomarker for high-risk patients with clinically- or radiologically-isolated neuroinflammatory syndromes.
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Affiliation(s)
- Colin R. Zamecnik
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - Gavin M. Sowa
- Department of Medicine, McGaw Medical Center of Northwestern University, Chicago, IL, USA
| | - Ahmed Abdelhak
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - Ravi Dandekar
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - Rebecca D. Bair
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - Kristen J. Wade
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - Christopher M. Bartley
- UCSF Weill Institute for Neurosciences, Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Asritha Tubati
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - Refujia Gomez
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - Camille Fouassier
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - Chloe Gerungan
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - Jessica Alexander
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - Anne E. Wapniarski
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - Rita P. Loudermilk
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - Erica L. Eggers
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - Kelsey C. Zorn
- Department of Biochemistry and Biophysics, University of California, San Francisco, CA, USA
| | - Kirtana Ananth
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - Nora Jabassini
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - Sabrina A. Mann
- Department of Biochemistry and Biophysics, University of California, San Francisco, CA, USA
| | - Nicholas R. Ragan
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - Adam Santaniello
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - Roland G. Henry
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - Sergio E. Baranzini
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - Scott S. Zamvil
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - Riley M. Bove
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - Chu-Yueh Guo
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - Jeffrey M. Gelfand
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - Richard Cuneo
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - H.-Christian von Büdingen
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - Jorge R. Oksenberg
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - Bruce AC Cree
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - Jill A. Hollenbach
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA USA
| | - Ari J. Green
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - Stephen L. Hauser
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - Mitchell T. Wallin
- Veterans Affairs, Multiple Sclerosis Center of Excellence, Washington, DC and University of Maryland School of Medicine, Baltimore, MD, USA
| | - Joseph L. DeRisi
- Department of Biochemistry and Biophysics, University of California, San Francisco, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - Michael R. Wilson
- UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
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Bingen JM, Clark LV, Band MR, Munzir I, Carrithers MD. Differential DNA methylation associated with multiple sclerosis and disease modifying treatments in an underrepresented minority population. Front Genet 2023; 13:1058817. [PMID: 36685876 PMCID: PMC9845287 DOI: 10.3389/fgene.2022.1058817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Accepted: 11/28/2022] [Indexed: 01/06/2023] Open
Abstract
Black and Hispanic American patients frequently develop earlier onset of multiple sclerosis (MS) and a more severe disease course that can be resistant to disease modifying treatments. The objectives were to identify differential methylation of genomic DNA (gDNA) associated with disease susceptibility and treatment responses in a cohort of MS patients from underrepresented minority populations. Patients with MS and controls with non-inflammatory neurologic conditions were consented and enrolled under an IRB-approved protocol. Approximately 64% of donors identified as Black or African American and 30% as White, Hispanic-Latino. Infinium MethylationEPIC bead arrays were utilized to measure epigenome-wide gDNA methylation of whole blood. Data were analyzed in the presence and absence of adjustments for unknown covariates in the dataset, some of which corresponded to disease modifying treatments. Global patterns of differential methylation associated with MS were strongest for those probes that showed relative demethylation of loci with lower M values. Pathway analysis revealed unexpected associations with shigellosis and amoebiasis. Enrichment analysis revealed an over-representation of probes in enhancer regions and an under-representation in promoters. In the presence of adjustments for covariates that included disease modifying treatments, analysis revealed 10 differentially methylated regions (DMR's) with an FDR <1E-77. Five of these genes (ARID5B, BAZ2B, RABGAP1, SFRP2, WBP1L) are associated with cancer risk and cellular differentiation and have not been previously identified in MS studies. Hierarchical cluster and multi-dimensional scaling analysis of differential DNA methylation at 147 loci within those DMR's was sufficient to differentiate MS donors from controls. In the absence of corrections for disease modifying treatments, differential methylation in patients treated with dimethyl fumarate was associated with immune regulatory pathways that regulate cytokine and chemokine signaling, axon guidance, and adherens junctions. These results demonstrate possible associations of gastrointestinal pathogens and regulation of cellular differentiation with MS susceptibility in our patient cohort. This work further suggests that analyses can be performed in the presence and absence of corrections for immune therapies. Because of their high representation in our patient cohort, these results may be of specific relevance in the regulation of disease susceptibility and treatment responses in Black and Hispanic Americans.
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Affiliation(s)
- Jeremy M. Bingen
- Neurology, University of Illinois College of Medicine, Chicago, IL, United States,Physiology and Biophysics, University of Illinois College of Medicine, Chicago, IL, United States
| | - Lindsay V. Clark
- High Performance Biological Computing, and Roy J Carver Biotechnology Center, University of Illinois, Champaign, IL, United States
| | - Mark R. Band
- High Performance Biological Computing, and Roy J Carver Biotechnology Center, University of Illinois, Champaign, IL, United States
| | - Ilyas Munzir
- Neurology, University of Illinois College of Medicine, Chicago, IL, United States
| | - Michael D. Carrithers
- Neurology, University of Illinois College of Medicine, Chicago, IL, United States,Physiology and Biophysics, University of Illinois College of Medicine, Chicago, IL, United States,Neurology, Jesse Brown Veterans Administration Hospital, Chicago, IL, United States,*Correspondence: Michael D. Carrithers,
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Liver kinase B1 rs9282860 polymorphism and risk for multiple sclerosis in White and Black Americans. Mult Scler Relat Disord 2021; 55:103185. [PMID: 34371271 DOI: 10.1016/j.msard.2021.103185] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 07/12/2021] [Accepted: 07/31/2021] [Indexed: 11/23/2022]
Abstract
BACKGROUND We previously reported that the single nucleotide polymorphism (SNP) rs9282860 in serine threonine kinase 11 (STK11) gene which codes for liver kinase B1 (LKB1) has higher prevalence in White relapsing-remitting multiple sclerosis (RRMS) patients than controls. However it is not known if this SNP is a risk factor for MS in other populations. METHODS We assessed the prevalence of the STK11 SNP in samples collected from African American (AA) persons with MS (PwMS) and controls at multiple Veterans Affairs (VA) Medical Centers and from a network of academic MS centers. Genotyping was carried out using a specific Taqman assay. Comparisons of SNP frequencies were made using Fisher's exact test to determine significance and odds ratios. Group means were compared by appropriate t-tests based on normality and variance using SPSS V27. RESULTS There were no significant differences in average age at first symptom onset, age at diagnosis, disease duration, or disease severity between RRMS patients recruited from VAMCs versus non-VAMCs. The SNP was more prevalent in AA than White PwMS, however only in secondary progressive MS (SPMS) patients was that difference statistically significant. AA SPMS patients had higher STK11 SNP prevalence than controls; and in that cohort the SNP was associated with older age at symptom onset and at diagnosis. CONCLUSIONS The results suggest that the STK11 SNP represents a risk factor for SPMS in AA patients, and can influence both early (onset) and later (conversion to SPMSS) events.
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Kharati M, Foroutanparsa S, Rabiee M, Salarian R, Rabiee N, Rabiee G. Early Diagnosis of Multiple Sclerosis Based on Optical and Electrochemical Biosensors: Comprehensive Perspective. CURR ANAL CHEM 2020. [DOI: 10.2174/1573411014666180829111004] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Background:
Multiple Sclerosis (MS) involves an immune-mediated response in which
body’s immune system destructs the protective sheath (myelin). Part of the known MS biomarkers are
discovered in cerebrospinal fluid like oligoclonal lgG (OCGB), and also in blood like myelin Oligodendrocyte
Glycoprotein (MOG). The conventional MS diagnostic methods often fail to detect the
disease in early stages such as Clinically Isolated Syndrome (CIS), which considered as a concerning
issue since CIS highlighted as a prognostic factor of MS development in most cases.
Methods:
MS diagnostic techniques include Magnetic Resonance Imaging (MRI) of the brain and spinal
cord, lumbar puncture (or spinal tap) that evaluate cerebrospinal fluid, evoked potential testing revealing
abnormalities in the brain and spinal cord. These conventional diagnostic methods have some
negative points such as extensive processing time as well as restriction in the quantity of samples that
can be analyzed concurrently. Scientists have focused on developing the detection methods especially
early detection which belongs to ultra-sensitive, non-invasive and needed for the Point of Care (POC)
diagnosis because the situation was complicated by false positive or negative results.
Results:
As a result, biosensors are utilized and investigated since they could be ultra-sensitive to specific
compounds, cost effective devices, body-friendly and easy to implement. In addition, it has been
proved that the biosensors on physiological fluids (blood, serum, urine, saliva, milk etc.) have quick
response in a non-invasive rout. In general form, a biosensor system for diagnosis and early detection
process usually involves; biomarker (target molecule), bio receptor (recognition element) and compatible
bio transducer.
Conclusion:
Studies underlined that early treatment of patients with high possibility of MS can be advantageous
by postponing further abnormalities on MRI and subsequent attacks.
:
This Review highlights variable disease diagnosis approaches such as Surface Plasmon Resonance
(SPR), electrochemical biosensors, Microarrays and microbeads based Microarrays, which are considered
as promising methods for detection and early detection of MS.
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Affiliation(s)
- Maryam Kharati
- Biomaterials Group, Faculty of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
| | - Sanam Foroutanparsa
- Biomaterials Group, Faculty of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
| | - Mohammad Rabiee
- Biomaterials Group, Faculty of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
| | - Reza Salarian
- Biomedical Engineering Department, Maziar University, Noor, Royan, Iran
| | - Navid Rabiee
- Department of Chemistry, Shahid Beheshti University, Tehran, Iran
| | - Ghazal Rabiee
- Department of Chemistry, Shahid Beheshti University, Tehran, Iran
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8
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Unmasking the Masquerader: A Delayed Diagnosis of MS and Its 4.5 Years of Implications in an Older African American Male. Case Rep Med 2019; 2019:5787206. [PMID: 31485233 PMCID: PMC6702817 DOI: 10.1155/2019/5787206] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2019] [Accepted: 07/25/2019] [Indexed: 11/17/2022] Open
Abstract
Multiple sclerosis (MS) has classically been described as a disease of the young Caucasian female. While the prevalence may seem to be higher in Caucasians (CAs), recent studies suggest that the real incidence of MS may actually be higher in African Americans (AAs). Here, we discuss a nonclassical case of MS in an older African American male, prognostic factors, disease patterns in African Americans, and how a delay in diagnosis and socioeconomic factors can lead to worse outcomes. In patients that present with possible symptoms of MS, a high suspicion for MS should be entertained even in epidemiologically atypical patients to prevent delay in diagnosis and irreversible disability.
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