Ankylosing Spondylitis: A Systematic Review of Demographics, Clinical Features, Biomarkers, and Risk Factors

0
4062

Abstract

Ankylosing Spondylitis (AS) is characterized as an autoimmune response that primarily affects the neck, spine joints, and sacroiliac joints. The aim of this study is to evaluate  the clinical features and provide  valuable insights into the complex nature of AS. PubMed literature searches were conducted to find AS patient information. The data included information from 212,490 patients diagnosed with AS from 71 literatures. The mean age of patients with AS was 55.1, 99.2% of patients had reported back pain, and 92.4% were HLA-B27 positive, all of which are consistent with previous studies observing patients with AS. This study found that 37.8% of patients with AS had family history of spondyloarthritis, which is more reliable as this study had a larger sample size. This study also found that 20.3% of patients with AS also had arthritis. This correlation was not investigated in most previous studies observing patients with AS, and should be further investigated in future studies.

Introduction

Overview of AS

AS is a medical condition that falls under the spondyloarthritis group of diseases. It is characterized by an autoimmune response that primarily affects the neck, spine joints, and sacroiliac joints. Individuals with AS commonly experience stiffness and discomfort originating from the lower back and progressing upwards towards the neck. This inflammation later leads to the spine completely fusing which results in immobility of the spine and neck.  The underlying cause is the fusion of ligaments and discs between the vertebrae, which is a result of the autoimmune nature of this condition1. Autoimmune diseases are defined by the body’s immune system mistakenly identifying its own healthy cells as potentially harmful foreign entities. In AS, instead of identifying and attacking foreign cells, the immune system attacks healthy tissue surrounding joints. This is what causes the fusion in the backs and necks of AS patients1.

Pre-existing Research

Previous patient data has shown a gender disparity among AS patients. AS is notably more common among males than females. As shown in a previous study, the number of males in the study was 8609 whereas the number of females was only 44352. AS has also shown to be most common in Caucasians. A study found that among participants, 2.25% were Asians, 8.38% were Black, 8.19% were Hispanic, 61.58% were White and the other 19.6% were not specified3. Evidently, the largest ethnic group within this study was Caucasian. Another factor that is of significance is age. A previous study demonstrates the distribution of AS patients in each age range as shown in Figure 1. This shows the mean age to be 49.1 with most patients being diagnosed after the age of 454.

Figure 1. The age distribution of diagnosis of AS4, mean age: 49.1,

Diagnosis of AS

AS can be a complicated condition to diagnose because there are no standard tests to determine whether or not a patient has AS5. As a result, finding trends in common clinical features including back pain and arthritis can help future AS patients get an earlier diagnosis. To initially diagnose AS, doctors may assess symptoms like back pain through a physical examination, which involves testing various movements of the spine and applying pressure to specific areas to locate the source of pain. Subsequently, magnetic resonance images (MRIs) and x-rays can reveal visible indications of ankylosing spondylitis such as arthritis. While there are no specific tests to identify AS, imaging and physical examinations can provide information regarding certain clinical features involved with AS6. Once such clinical features have been identified, patients can get an AS diagnosis. 

Prognosis of AS

In addition to looking at clinical features, doctors may look at risk factors such as family history. It has been shown that AS is more likely to occur in patients who have a first degree relative already affected by AS7. Similarly, doctors may look at the HLA-B27 gene as there has recently been found to be a correlation between HLA-B27 positivity and AS diagnosis. HLA-B27 (Human Leukocyte Antigen B27) is a protein found on the surface of white blood cells. It helps the body differentiate between its own cells and foreign cells. To test for HLA-B27, doctors run a blood test and determine whether or not a patient is HLA-B27 positive. If a patient is positive, they are at a higher risk for certain autoimmune diseases including AS 8. By looking at such risk factors associated with this condition, doctors may be able to efficiently predict the development of AS within a patient or family.

Biomarker of AS

The most prominent biomarker for AS  is  the  presence of HLA-B27. Blood tests can help determine if the patient carries HLA-B27, which is present in 80-90% of AS patients. However, being HLA-B27 positive does not guarantee the presence of AS9. Looking at this biomarker combined with clinical features can contribute to a more accurate diagnosis of AS. In addition to HLA-B27, ERAP-1 and MMP-3 are biomarkers that have recently been linked to AS. Prior research on ERAP-1 observes that ERAP-1 is only associated with AS in patients that are HLA-B27 positive as well. Research indicates that within AS patients, single nucleotide polymorphisms (SNP) are present in the ERAP-1 gene. Specifically, there seems to be a correlation between ERAP-1 rs27044 SNP in AS patients of Asian and  European populations. Studies have also suggested a correlation between a protein called serum MMP-3 and AS in patients with joint swelling. The level of serum MMP-3 seems to relate to the severity of inflammation in patients with forms of arthritis. MMP-3 levels have been found to correspond with disease activity in spinal and peripheral symptoms of AS10. Studying this correlation can be useful for AS diagnosis and treatment. 

Aim of study

Our research focuses on the patient data of those who have been diagnosed with AS. The information covered includes demographics, clinical features, biomarkers, and risk factors associated with AS. Demographics include data about patients’ age, gender, ethnicity, and race. Risk factors include family history. Clinical features include patients’ symptoms such as arthritis and back pain. Biomarkers include the presence of HLA-B27 in AS patients. This study aims to evaluate the clinical traits that may assist in the diagnosis of AS in future patients. Prior research on this condition fails to provide a concise, comprehensive analysis of multiple features of AS. For example, it should be noted that while past reviews have included a lot of information about HLA-B27, they have put less emphasis on the correlation between arthritis and AS, and the significance of arthritis as a clinical feature for this condition. This review aims to provide a more inclusive analysis of the different factors that may contribute to the development of AS in patients.

Results

Demographics

The  study  included information from  212,490 patients diagnosed with AS from 71 literatures. 66,377 were  males, 23,503 were  females, and 122,611 patients with unknown gender information. Our findings reflect AS to be more prominent in males than females: 73.9% versus 26.1% respectively . The mean age of diagnosis is 55.1 years old, with ages ranging between 18 and 91. As for correlation with race/ethnicity, as shown in Figure 2, there are  94,952 (87.2%) White patients, 7,332 (6.7%) Black patients, 3,466 (3.2%) Hispanic patients, 3,107 (2.9%) Asian/Pacific Islander patients, and 84 (0.077%) Native American/Alaskan Native patients (too small to see in Figure 2).

Figure 2. The ethical distribution of patients with AS not including patients whose race data was unavailable. 94,952/212,490 (87.2%) patients were White, 7,332/212,490 (6.7%) patients were Black, 3,466/212,490 (3.2%) patients were Hispanic, 3,107/212,490 (2.9%) patients were Asian/Pacific Islander, and 84/212,490 (0.077%) patients were Native American/Alaskan Native

Biomarkers

To study the biomarkers, we examined the prevalence of the HLA-B27 positivity in the AS participants . We found that 10,651 patients had available HLA-B27 tests of which 9,845 patient tests reported them to be HLA-B27 positive. This resulted in a 92.4% prevalence of HLA-B27 in our data set.

Risk Factors

The risk factor  investigated in the present study includes   family history for conditions in the spondyloarthritis group. Of the 983 patients who had family history data available, 372 reported having family members who were already diagnosed with some form of spondyloarthritis, indicating  a 37.8% occurrence of family history being a risk factor in this data set.

Clinical Features 

As shown in Figure 3, 5,041 patients had available data regarding back pain of which 5,000 patients were reported to suffer with back pain. This resulted in a 99.2% occurrence of back pain in our data set. As for arthritis, 2,299 patients had available data regarding arthritis of which 467 were reported to have arthritis. This resulted in a 20.3% occurrence of arthritis in this data set.

Figure 3.  The distribution of patients with symptoms not including the patients whose data for these clinical features was unavailable. 5,000/5,041 (99.20%) patients reported back pain and 2,299/5,041 (20.3%) patients were diagnosed with arthritis.

Discussion

Demographics

The demographic characteristics of AS patients vary across different populations. This study only includes information from adult patients. This is consistent with previous studies that have identified AS as typically being diagnosed in adulthood for most patients. This can also be the result of recruitment bias as other studies mainly focus on adult patients with AS. Also consistent with previous studies, our data set shows a much higher number of male patients than female patients. This can be due to less patient data available for women than there is for men. As for  race and ethnicity of  AS epidemiology, AS is present  in diverse racial and ethnic groups, but our research shows its high prevalence in the white population. (Figure 2), which represents  87.2%. Nevertheless, this can be attributed to recruitment bias. 

Clinical Features

Back pain is a significant feature of AS. Our review showed that  back pain is a primary symptom. Previous studies show 92.7-100% of AS patients also have back pain, which is consistent with the findings in this study11,12. Nevertheless, since patients may only be referred for diagnosis of AS only when back pain is present, this can be a recruitment bias for diagnosis of AS. This may also explain why this study found such a high occurrence of back pain in AS patients. Arthritis is another key clinical feature of AS. While most previous studies did not investigate the association between arthritis and AS, our analysis highlights the frequency of arthritis in AS patients. Because arthritis is also a condition that affects bones and joints, the association between arthritis and AS can be significant in AS diagnosis and can lead to answering more questions about the cause of AS. It can also be a useful tool in the diagnosis of AS as the correlation between arthritis and AS is studied more in the future..

Biomarkers

Around 8% of the general population is HLA-B27 positive and around 80-90% of AS patients are HLA-B27 positive9. Consistent with these numbers, our data set had over a 90% prevalence of HLA-B27. The association between HLA-B27 positivity and the development of AS is notable across a number of studies and can be extremely beneficial in AS diagnosis as well. HLA-B27 also contributes to the heritability of AS, which makes it more likely to be passed onto future generations. This aspect of HLA-B27 also relates to the genetic aspect of this disease and may help establish a correlation between AS and genetics in the future.

Risk Factors

Risk factors, such as family history, can contribute to the development of AS. Previous studies show 11.9-62.2% occurrence of family history within AS patients13,14. These studies provided a large range of occurrences for this risk factor. The present study has a larger sample size and hence provides more reliable data about family history. As this study aims to provide a more comprehensive analysis of the factors affecting AS development, the narrower results show a more reliable occurrence of family history in AS patients than previous studies. As more data is collected regarding family history and the role it plays in AS development, this risk factor can also be used as a tool for early AS diagnosis and treatment.

Limitations

A limitation of our research was the lack of individual patient data available. Many studies had information regarding the condition, but didn’t have information about each patient. We specifically lacked access to detailed age distribution from studies.  This restricted our access to data that could be analyzed for our research. Furthermore, many data sets had recruitment biases in gender, race, and age. Most literature studied in this systematic review only had data on males over females. All literature studied in this systematic review had more white patients than other racial/ethnic groups and only had data for adults. This made it difficult to have a fully representative data set in our own study. Therefore, future studies can be improved by including complete gender data from both males and females, have similar distribution of different racial/ethnic groups, and should also include data from younger (below 18) age groups. Additionally, this review only includes literature from the PubMed database, written in English, and including patient data from the United States as these were the most accessible in this study. Because of this, another limitation of this study is that it is only representative of the U.S. AS patient population rather than the population of AS patients globally. Patient data was also only used if it was provided for individual patients rather than a population of patients. This ensured that all data was more precise and accurate, but also reduced the number of literatures that were included.

Methods

PubMed literature searches were conducted using the key word search [“ankylosing spondylitis” AND (“HLA-B27” OR “back pain” OR “arthritis”) AND “US”]. The search was executed on August 6, 2023. The initial search yielded 294 matches. Of which, 45 articles were inaccessible and consequently excluded. An additional 164 articles were omitted due to their deficiency in relevant AS patient data. Furthermore, 14 articles were disregarded for not being authored in English. The remaining 71 literatures were used as shown in the PRISMA flowchart in Figure 4. PRISMA guidelines were followed when determining which literatures would be included in this study, collecting the data, and analyzing the data.   Patient data collected from these literatures included patient age, gender, race/ethnicity, occurrence of back pain, presence of arthritis, presence of HLA-B27, and occurrence of family history. Using this data an analysis was conducted to determine the mean age, range of ages, ethnic distribution, presence of back pain, arthritis, and presence of HLA-B27.

Figure 4. PRISMA Flowchart with literature exclusion process.

Conclusion

In conclusion, this systematic review provides a comprehensive synthesis of AS demographics, clinical features, biomarkers, and risk factors. By analyzing the patient data collected from other literatures, we found traits that may support patterns in the general AS population. We found the mean and range ages of our data set, the gender distribution, racial/ethnic distribution, occurrence of back pain and arthritis, presence of HLA-B27, and existence of family history within our data set. A key finding of this study is that 20.3% of patients in this data set had arthritis, which was seldom reported in previous studies. An increase in data to support the association between AS and arthritis may serve as a helpful diagnosis tool in the future. Because of this, it would be beneficial for future studies to emphasize the study of the relationship between arthritis and AS. It was also found that a higher percentage (92.4%) of patients with AS in this study were HLA-B27 positive compared to previous studies. This strong association is consistent with the findings of past studies as well and may serve as an important indicator of AS. Another key finding was a 37.8% occurrence of family history within AS patients. This is more reliable data than previous studies as it offers a narrower, more precise percentage rather than a range of occurrence of family history. It would also be beneficial for future studies to focus on this risk factor as past studies had limited data about it and it can be a key indicator of AS.

Acknowledgements

Huairen Zhang

Ankylosing Spondylitis: A Systematic Review of Demographics, Clinical Features, Biomarkers, and Risk Factors Supplementary Table

PMID# of patientsFemaleMaleAgeEthnicity/RaceBack PainArthritisHLA-B27Family history
269873413336NANArange: 18-64 mean: 44.7NA3336NANANA
259178497772NANANANANANA7772 (they only looked at HLA-B27 positive patients in the study) 
30210584356NANANANAall patients with back pain Visual Analog Scale (VAS) score of ?4NANANA
27445458620NANANANANANANANA
29409123310NA200mean +/- SD (49.2 ± 14.3), 18 and olderwhite=279, asian=6, black=5, pacific islander=1, mixed race=4, other=3310NAPatients with available HLA–B27 test results (reported on laboratory form):154 Positive test result (among patients with available test results): 102 HLA–B27 positivity (physician reported):20037
26628601428815302758mean: 49.1 (SD:13.4), 18-34: 649, 35-44: 906, 45-54: 1199, 55-64: 1101, 65 and up: 433NANANANANA
35672618646272374mean: 42.88, SD: 13.2, 18–39:273, 40–64:344 ,65–74 :19, ?75: 10NANANANANA
18383414591NANA18-87 mean age: 48.9NANANANANA
34564835177948649NAmean: 57.2asians: 401 black: 1492 white: 10957 hispanic: 1457 not specified: 3487NANANANA
18357499216NANAage: 18-70, mean: 38.1?±?10.6NANAPeripheral arthritis was present in 29.4% of patients. Hip joint: 9.3% knee joint: 8.5% shoulder joint: 6.1%HLA-B27 was investigated in 31.1.% of patients. Rate of positivity was 91%NA
2865270386NANANANANANANANA
27790010315NANANANAtotal back pain score ?4 cm (on a 0–10 cm visual analog scale [VAS]NANANA
357688801094057605180 white: 8900 black: 940 other: 1100NANANANA
30260423792950Mean: 44.4 (SD 11)NANANA44/65 (67.7%)NA
2966698029NANANANANANANANA
3244229513,0444435860965 (all data came from medicare enrollment)white:11,858 black:514 other:672NANANANA
3445956543872366?24: 61 25–34 :164 35–44 :144 ?45: 69 Mean ± SD (median)‡ 34.69 ± 8.63 (34)White :307 Black :84 Asian or Pacific Islander: 24 Other, mixed or unknown:23406 patients with lower back painNANANA
334521682057946NAMean: 58.2NANA417 (rheumatoid arthritis)NANA
36333490581238NAMean:50.2Caucasian: 411NANANANA
3360738563917946050 ±?12NANANA460 positiveNA
26337538151948NA18-34: 180, 35-44: 257, 45-54: 354, 55-63: 514, >63: 214NANANANANA
33858974414156252NANANANANANA
31663467935NA886mean: 57.6ETHNICITY – hispanic: 38 non-hispanic: 866 unknown: 31 RACE – white: 732 black: 103 other: 59 unknown: 41NANANANA
31371654119NA82mean: 50.85 ± 14.77white: 96 other: 23NANANANA
308682872254NANANANANANANANA
3548133350173362-73, median: 68NANANANANA
2996169352,568NANAmean: 59.3 ± 11.4 yearsNANANANANA
36001102334206128mean: 54.4, SD: 14.3white: 282n=285, mild: 72, moderate/severe: 203NANANA
877785910135NA1NANANA
3037126442,327NA26,796Age 65–69 y: 11 477 Age 70–74 y: 9097 Age 75–79 y: 8631 Age 80 y or older: 13 122White: 38,167 Black: 1863 Hispanic: 542 Asian: 776 Other: 979NANANANA
295891321178NA834mean: 36.57, SD:12.78all chineseNANA752 positiveNA
29196383706NANANANANANANANA
3104166623517461mean: 49.8white: 218 black/african american: 5 american indian/alaska native: 5 asian: 0 unknown: 2NANANANA
300943881690326946NAETHNICITY- hispanic/latino: 94, not:1178 RACE-white:1033, black: 49, asian: 86, Native American Indian or Alaskan Native (Hispanic): 75, Native Hawaiian or Other Pacific Islander: 0, mixed race: 28, unknown: 1NANANANA
3198518124NANA37.5 ± 5.6NANANANANA
30353387155NA114mean: 47.9white: 140, asian: 3, black: 2, pacific islander: 0, mixed race: 3, other: 1NANAPatients with available HLA-B27 test result: 108, Positive test result (among patients with available test results): 80Family history of SpA: 23
291420401150NANANANANANANANA
296691972773NANAyounger than 75, 61.1 ± 10.8NANANANANA
3356819180NANANANANANANANA
16082640169NANAmean: 38-43NANANANANA
281095772882051 ± 12.31NANANANANA
18512723397NANANANANANANANA
269907311011NANANANANANANANA
3008811514,714NA880441.8 ± 11.9white: 9471, black: 1722, hispanic: 1377, asian: 572, other: 1572NANANANA
233344253616NA35.2 ± 8.9NANANANANA
2283624410132whiteNANA1NA
1222816127NANANANANANANANA
312218847686NANAmean:44.6NA16%NANANA
3647075212,451NA819365 and upwhite: 11282, black: 501, other: 668NANANANA
288910053503535.17 ± 8.05NANANANANA
2360454710142NAyesNApositiveno
3299936213211mean: 50 range: 47-67NANANA9/13 (69.2%)NA
22257916493NANANANANANANANA
22231927502NANANANANANANA312
19369461100NANAmean: 61 ± 13NANANANANA
36153800409196213mean: 54.5?±?16.2 median: 55 range: 19-89 age groups: 0-17: 0 (0%) 18-44: 116 (28.4%) 45-64: 169 (41.3%) 65-74: 76 (18.6%) 75-84: 38 (9.3%) 85+: 10 (2.4%)RACE- Caucasian: 328 (80.2%) African American: 40 (9.8%) Asian: 9 (2.2%) Other/Unknown: 32 (7.8%) ETHNICITY- Hispanic: 31 (7.6%) Not Hispanic: 355 (86.8%) Unknown: 23 (5.6%)NANANANA
21360492158NANAolder than 18NANANANANA
2922262522NANANANANANANANA
3105658210136NANANApositiveNA
301579251254778Age at time of study (years), mean?±?SD: 48.3?±?9.6 Age at time of diagnosis (years), mean?±?SD: 39.5?±?9.6NANANA92 (74.8%)NA
1250961444044mean:44+/-12JapaneseNANANANA
11727838511239mean:46.8NANANA45 positiveNA
1793813715015range:51-91NANANA00
16208654326NA24155.0 ± 10.7white: 284 (87.1%) african-american: 12 (3.7%) asian/pacific islander: 7 (2.1%) native american: 4 (1.2%) hispanic: 17 (5.2%) other: 2 (0.6%)NANANANA
938266823815NANANANANANA
11817595241NA16747.1 +/- 13.8206 whiteNA49 peripheral arthritisNANA
3212412852717635139.9 ± 12.7NANANA485 positiveNA
2896620618NA16mean: 44NANANANANA
2874224110150NANAosteoarthritis in the lower lumbar spineNANA
16169767215NANANANANANANANA
8635287101NANANANApositiveNA
  1. Better Health Channel, Better Health Channel Website, Australian government, accessed 26 August 2023, <https://www.betterhealth.vic.gov.au/health/conditionsandtreatments/ankylosing
    -spondylitis
    > [] []
  2. Ward, M.M. and Alehashemi, S., 2020. Risks of solid cancers in elderly persons with osteoarthritis or ankylosing spondylitis. Rheumatology, 59(12), pp.3817-3825. []
  3. Ogdie, A., Matthias, W., Thielen, R.J., Chin, D. and Saffore, C.D., 2021. Racial differences in prevalence and treatment for psoriatic arthritis and ankylosing spondylitis by insurance coverage in the USA. Rheumatology and therapy, 8, pp.1725-1739. []
  4. Greenberg, J.D., Palmer, J.B., Li, Y., Herrera, V., Tsang, Y. and Liao, M., 2016. Healthcare resource use and direct costs in patients with ankylosing spondylitis and psoriatic arthritis in a large US cohort. The Journal of rheumatology, 43(1), pp.88-96. [] []
  5. National Institute of Arthritis and Musculoskeletal and Skin Diseases May 2023, National Institute of Health Website, United States government, accessed 26 August 2023, <https://www.niams.nih.gov
    /health-topics/ankylosing-spondylitis/diagnosis-treatment-and-steps-to-take#:~:text=At%20this%20time%2C%20no%20single,information%20when%20making%20a%20diagnosis
    > []
  6. Health Central 23 February 2023, Health Central Website, accessed 26 August 2023, <https://www.healthcentral.com/condition/ankylosing-spondylitis/ankylosing-spondylitis-test> []
  7. van der Linden, S.M., Khan, M.A., Li, Z., Baumberger, H., van Zandwijk, H., Khan, M.K., Villiger, P.M. and Brown, M.A., 2022. Recurrence of axial spondyloarthritis among first-degree relatives in a prospective 35-year-follow-up family study. RMD open, 8(2), p.e002208. []
  8. Mount Sinai, Mount Sinai Website, Mount Sinai Health System, <https://www.mountsinai.org
    /health-library/tests/hla-b27-antigen#:~:text=HLA%2DB27%20is%20a%20blood,cells%20and%20foreign%2C%20harmful%20substances
    > []
  9. Spondylitis Association of America, Spondylitis Association of America Website, accessed 26 August 2023, <https://spondylitis.org/spondylitis-plus/blood-work-in-ankylosing-spondylitis/> [] []
  10. Danve, A. and O’Dell, J., 2015. The ongoing quest for biomarkers in Ankylosing Spondylitis. International Journal of Rheumatic Diseases, 18(8), pp.826-834. []
  11. Nelson, D.A., Kaplan, R.M., Kurina, L.M. and Weisman, M.H., 2023. Incidence of ankylosing spondylitis among male and female United States Army personnel. Arthritis Care & Research, 75(2), pp.332-339. []
  12. Deodhar, A., Mittal, M., Reilly, P., Bao, Y., Manthena, S., Anderson, J. and Joshi, A., 2016. Ankylosing spondylitis diagnosis in US patients with back pain: identifying providers involved and factors associated with rheumatology referral delay. Clinical rheumatology, 35, pp.1769-1776. []
  13. Mease, P.J., Heijde, D.V.D., Karki, C., Palmer, J.B., Liu, M., Pandurengan, R., Park, Y. and Greenberg, J.D., 2018. Characterization of patients with ankylosing spondylitis and nonradiographic axial spondyloarthritis in the US?based Corrona Registry. Arthritis care & research, 70(11), pp.1661-1670. []
  14. Joshi, R., Reveille, J.D., Brown, M.A., Weisman, M.H., Ward, M.M., Gensler, L.S., Wordsworth, B.P., Evans, D.M. and Assassi, S., 2012. Is there a higher genetic load of susceptibility loci in familial ankylosing spondylitis?. Arthritis care & research, 64(5), pp.780-784. []

LEAVE A REPLY

Please enter your comment!
Please enter your name here