Skip to main content

Optical coherence tomography findings in children of patients with Alzheimer-type dementia

Abstract

Background

Ocular imaging receives much attention as a source of potential biomarkers for dementia. This study aims to study structural changes in the retina and optic nerve in children of healthy and demented parents and to confirm the applicability of optic nerve tomography as a potential noninvasive marker for the early diagnosis of dementia.

Methods

Healthy individuals with a parent diagnosed with Alzheimer’s disease (AD) and healthy controls with healthy parents were included in the study. Included individuals had undergone Montreal Cognitive Assessment Scale and Mini-Mental Test by a single neurologist physician to confirm not having dementia. All the subjects then underwent a complete ophthalmological examination, including refractive error and keratometry readings, best-corrected visual acuity measurement with a Snellen chart (converted to LogMAR), intraocular pressure (IOP) measurement, slit-lamp biomicroscopy, dilated fundus examination, axial length measurement and optical coherence tomography (OCT) for the parapapillary retinal nerve fiber layer (pRNFL), basal membrane opening—minimum rim width (BMO-MRW), and macular thickness analysis. Only the right eyes of the subjects were evaluated. OCT findings of these two groups were compared.

Results

The temporosuperior sector the pRNFL thicknesses at all 3 circles (3.5, 4.1, and 4.5) were significantly thinner in the children of the dementia group than in healthy controls (p = 0.023, 0.039, and 0.016, respectively). For the remaining sectors, the thicknesses of the pRNFL were also thinner, however, the differences were not significant (p > 0.05 for all). BMO-MRW at all sectors, were not also different significantly between the groups (p > 0.05 for all). Parents’ dementia grade were found to be an important factor that the BMO-MRW at the temporal sector, got thinner with increasing grade (B = − 20.631, 95% CI − 42.121 to − 0.019, and p = 0.049).

Conclusion

We believe that OCT can be used as a noninvasive biomarker in the preclinical period, when supported by more extensive studies in people whose parents have AD.

Introduction

Cognitive impairment is major medical, social, and economic public health issue worldwide with significant implications for life quality in adults. The population continues to age and the prevalence of Alzheimer disease (AD) is expected to grow. At present, there is no curative treatment for AD. A definitive diagnosis of AD can only be made through histopathologic examination. Recent investigations have explored whether the structural changes of the retina and optic nerve can provide screening for early detection of AD [1, 2]. Economic, social problems caused by AD reveal the importance of early diagnosis and treatment of the disease. Ophthalmologic impairments have also been reported in AD. These symptoms of visual dysfunction in AD have been associated with the degeneration of anterior visual pathways. There are many research articles in the literature on these two topics [3, 4]. Based on these articles, we compared the pRNFL and BMO-MRW in the children of individuals with dementia with a control group of similar age and gender. Recognition of the disease in the pre-symptomatic period will contribute to the study of etiopathogenesis and neuroprotective therapy. The data obtained from these studies will be used to solve economic, social and individual problems caused by AD. This study aims to study structural changes in the retina and optic nerve in children of healthy and demented parents and to confirm the applicability of optical nerve tomography as a potential noninvasive marker for the early diagnosis of AD. We think that OCT has a promising role in this phase.

Methods

Subjects and methods

The study was a cross-sectional prospective study approved by Hitit University School of Medicine Ethics Committee (349/2021) and conducted by STROBE guidelines for reporting observational studies (www.strobestatement.org) and the Declaration of Helsinki. All participants gave their informed consent for this study. Individuals between the ages of 25 and 65 with a diagnosis of mild or moderate AD in one of their parents were included in the study. On the other hand, individuals of similar age and gender whose parents were cognitively healthy were selected for the control group. Excluded from the study were the individuals diagnosed with dementia based on clinical anamnesis and examination findings, patients with ocular pathologies (cataract, glaucoma, corneal diseases, such as dry eye and > 3D astigmatism, retinal diseases, uveitis, or ocular surgery history), those with systemic diseases that could cause changes to the ocular and neurological physiology (diabetes mellitus, connective tissue diseases, and autoimmune diseases), and those with OCT artifacts and anatomic variations such as insufficient OCT quality (quality score < 20), segmentation errors, vitreoretinal interface problems, optic disc drusen, and chorioretinal scarring. Healthy individuals with a parent (mother and/or father) diagnosed with AD according to the criteria of the National Neurological and Communication Diseases and Stroke Institute/Alzheimer’s Disease and Related Disorders Association and healthy controls with healthy parents included in the study. Included subjects were undergone Montreal Cognitive Assessment Scale and Mini-Mental Test by a single neurologist physician to confirm not having dementia. All participants also underwent a complete ophthalmological examination, including refractive error and keratometry readings (Tonoref III, Nidek Co. Ltd, Aichi, Japan), best-corrected visual acuity assessed using a Snellen chart (converted to LogMAR), intraocular pressure (IOP) measurement, slit-lamp biomicroscopy, dilated fundus examination, axial length measurement (AL-SCAN, Nidek Co. Ltd, Aichi, Japan), and OCT (Spectralis OCT Heidelberg Engineering, Heidelberg, Germany) for pRNFL thickness, BMO-MRW, and macular thickness analysis. The parents of the volunteers in both groups participating in the study underwent a complete eye examination. Only the right eyes of the subjects were evaluated. OCT findings of these two groups were compared.

Analyses of the OCT measurements

Spectralis OCT was used for the measurement of the BMO-MRW and pRNFL thicknesses. This device has a scan rate of 40,000/s using a light source of 820 nm. For both pRNFL and the BMO-MRW thickness measurements, glaucoma module premium edition software was used. For each eye with non-dilated pupil, automated anatomically positioning system detects the fovea center and Bruch’s membrane opening center, thereby preventing incorrect measurements due to the torsion of the eyes. After detection of the foveal center, two scan patterns were obtained: optic nerve head (24 radial scans centered on BMO) and peripapillary scans (3 concentric circle scans of 3.5, 4.1, and 4.5 mm in diameter). BMO-MRW was defined as the shortest distance between the BMO and the internal limiting membrane. For the pRNFL evaluation, a 12° circular scan was used to measure pRNFL thickness. Global and six sectors of (superotemporal, temporal, inferotemporal, inferonasal, nasal, superonasal) RNFL thicknesses from the 3 circles and BMO-MRW parameters were measured automatically by the device.

Statistical analysis

The sample size of the study was calculated using G*Power software (ver. 3.1.9.4 Dusseldorf, Germany) (for the difference between two different means; effect size d: 0.60; medium to large effect, α error: 0.05, power: 0.95, allocation ratio: 1, total sample size: 146). Jamovi ver. 1.6 (computer software, https://www.jamovi.org) was used for statistical analysis. Quantitative variables were defined as mean and standard deviation (sd) and qualitative variables as percentages. The Shapiro–Wilk test was used to evaluate whether the sample came from a normally distributed population. According to the results of the normality analysis, the pRNFL and BMO-MRW were compared between the groups using the parametric Student’s t-test or non-parametric Mann–Whitney U test. The distribution of the nominal and ordinal factors, such as gender was compared between the groups using Pearson’s Chi-squared test. After the collinearity diagnostics, a linear regression model was created for each pRNFL of the 4.1 mm diameter circle and BMO-MRW sector to explore the associations of the pRNFL and BMO-MRW thickness with age, OCT quality score, and BMO area as coefficients, and gender and group as factors. The dementia grade of the parents was also used as a factor only for the children of the dementia population. Results of the regression models were given with regression coefficient (R2), estimate (B), confidence interval (CI), and p values. A p value less than 0.05 considered statistically significant.

Results

Demographic data and clinical findings

A total of 81 subjects with a parent with dementia (Group 1) and 76 healthy volunteers (Group 2) were included in this study. There was no missing data of the study subjects. There were remaining 76 eyes in group 1 and 74 eyes in group 2. The groups showed similar distribution concerning age and gender (p = 0.471, and 0.404, respectively). The average age of the group with Alzheimer’s parents was found to be 45.93 + 10.21. 53.9% of the participants were women and 46.1% were men. In this group, 30 of the parents had mild and 46 had moderate AD. In the control group, the average age was found to be 44.91 + 8.79, while 54.1% of the participants were female and 45.9% were male.

There was no significant difference between the groups in terms of the IOP, BMO area, and quality of the OCT scanning (p = 0.239, 0.255, and 0.199, respectively). The demographic data are shown in Table 1.

Table 1 Demographic data and the clinical findings of the study participants

Results of the spectral domain OCT scanning

The mean values with sd of the pRNFL and BMO-MRW thicknesses for all sectors and the results of the comparisons between the groups are presented in Tables 2 and 3, respectively. Only for the temporosuperior sector the pRNFL thicknesses at all 3 circles (3.5, 4.1, and 4.5) were significantly thinner in the children of the dementia group than in healthy controls (p = 0.023, 0.039, and 0.016, respectively). For the remaining sectors, the thicknesses of the pRNFL were also thinner; however, the differences were not significant (p > 0.05 for all). BMO-MRW at all sectors, were not also differ significantly between the groups (p > 0.05 for all). However, the healthy controls had slightly thicker BMO-MRWs than the children of dementia parents. The results of the linear regression models for pRNFL thickness and BMO-MRW sectors are given in Tables 4 and 5, respectively. Regression analysis revealed that the pRNFL thickness and BMO-MRW were all associated with the BMO area (the true anatomical optic disc size) except for the inferonasal and the nasal sectors of the pRNFL (p = 0.201 and 0.194 for inferonasal and nasal sectors, respectively, and < 0.05 for the remaining). At the temporosuperior sector pRNFL thickness found to be thinner in the children of dementia independent from age, gender, BMO area, and the quality of the OCT scanning (B = − 5.690, 95% CI − 12.349 to – 0.871, and p = 0.039). Parents’ dementia grade were found to be an important factor that the BMO-MRW at the temporal sector, got thinner with increasing grade (B = − 20.631, 95% CI − 42.121 to − 0.019, and p = 0.049). The OCT quality score was found not to be associated with both pRNFL thickness and BMO-MRW at any sector.

Table 2 The mean pRNFL thicknesses of the sectors
Table 3 The mean BMO-MRW of the sectors
Table 4 Results of the regression models which searched for the associations with the pRNFL thickness
Table 5 Results of the regression models which searched for the associations with the BMO-MRW

Discussion

AD is the most common neurological disorder worldwide, and it is estimated that 1 in 3 of those born in developed countries today will develop dementia during their life [5]. AD is a progressive neurodegenerative disorder characterized by impairment of cognition and behavior, with significant physical, psychological, social, and economic implications. The main hallmark of AD is the accumulation of extracellular amyloid-beta (Aβ) plaques and intracellular tau neurofibrillary tangles comprising phosphorylated tau protein resulting in profound brain atrophy. Previous studies have indicated that vascular risk factors affecting the cerebral microcirculation may also contribute to AD pathogenesis, and microvascular pathologies are present in the majority of AD patients [6]. The diagnosis of AD is primarily clinical and relies on neuropsychological evaluation, as biomarker detection relies on examination of cerebrospinal fluid (CSF) and positron emission tomography (PET) scan, costly and invasive procedures that pose risks to patients [7]. At present, there is no curative treatment for AD. As most of the trials so far have focused on patients already suffering from AD, it is postulated that more success may be achieved by targeting those who still are cognitively intact [8, 9]. This poses a new problem. How can we recognize those at risk for the development of AD when there are no clinical symptoms yet? PET scanning has provided a breakthrough in diagnosing these cases of preclinical AD. The process of Aβ accumulation in the brain is a gradual one, which often has been ongoing for decades before the onset of clinical symptoms [10]. By using tracers sensitive to Aβ, PET enables visualization of Aβ presence in vivo in cognitively healthy individuals. The presence of Aβ deposits in the brain of healthy individual is a risk for developing AD [11, 12]. However, as reliable as this technique may be, it is currently not suitable for large-scale screening. It is a costly diagnostic procedure that is only available in larger hospitals [13]. This illustrates the urgent need for an easy, noninvasive and reliable biomarker for preclinical AD. The eye, and more specifically the retina, shares many similarities with the brain. Both are derived from the same embryological tissue and consist of a complex combination of neuronal tissue and glial cells. One could consider the retina to be an extension of the brain [14, 15]. Many studies have already illustrated changes in the retina of individuals suffering from AD, such as retinal thinning and vascular changes [16, 17]. A study in return close follow-up OCT and OCT angiography show great potential as noninvasive technologies for the diagnosis of AD. However, further research is needed to determine whether there are AD specific patterns of structural or microvascular change in the retina and optic nerve that distinguish AD from other neurodegenerative diseases. Development of sensitive and specific OCT/OCT angiography parameters will be necessary before they can be used to detect AD in clinical settings [18]. OCT, OCT angiography, fundus photography, and dynamic vessel analyzer are new imaging methods providing a quantitative assessment of retinal structural and vascular indicators such as thickness of the inner retinal layers, retinal vessel density, foveal avascular zone area, tortuosity and fractal dimension of retinal vessels, and microvascular dysfunction-for cognitive impairment and dementia. Should further studies need to be conducted, these retinal alterations may prove to be useful biomarkers for screening and monitoring dementia progression or early diagnosing in clinical routine [19]. Results of the literature provide evidence of the potential use of OCT-measured parafoveal granular cell layer-inner plexiform layer (GCIPL) thickness to monitor neurodegeneration and to predict the risk of cognitive worsening over time [20]. Many people with dementia-diagnosed parents always have the same question in mind. Am I going to have dementia too? Our answers to this question especially for children who take care of parents with dementia, are very limited. Our aim in the study was to seek an answer to this question. As a matter of fact, we obtained statistically positive results.

A retrospective study showed that GCIPL thickness best correlated with memory, global cognitive performance, clinical dementia rating, and hippocampal atrophy [21]. Many studies have detected changes in different layers of the retina in patients with mild cognitive impairment [22, 23]. Thinning of the GCIPL has also been associated with cognitive deterioration in Parkinson’s patients [20]. In another population-based study, Girbardt et al. report that thinner RNFL thickness was found to be a meaningful index for poorer cognitive performance which presents the potential for prediction of future cognitive decline [24]. In our study, retinal and optic nerve structures of cognitively normal individuals but whose parents have dementia were evaluated and significant statistical results were obtained. In our study, our goal was to detect abnormal findings in the OCT of people whose parent’s had Alzheimer's dementia. In the group whose parents had AD, we found at the temporosuperior sector pRNFL thickness found to be thinner in the children of dementia parents independent from age, gender, BMO area, and the quality of the OCT scanning. Parents’ dementia grades were found to be an important factor that the BMO-MRW at the temporal sector, got thinner with increasing grade. One of the limitations of our study, in which we took only one volunteer individual from each family, was that we did not extract detailed genetic genealogies of the families. Genetic tests for AD in our country, or the evaluation of markers in cerebrospinal fluid, are expensive and limited. This is an important reason for the restriction in our work.

Conclusion

We believe that OCT can be used as a noninvasive biomarker in the preclinical period, when supported by more extensive studies in people whose parents have AD.

Availability of data and materials

The authors confirm that the data supporting the findings of this study are available within the article [and/or] its additional materials.

Abbreviations

AD:

Alzheimer’s disease

OCT:

Optical coherence tomography

pRNFL:

Parapapillary retinal nerve fiber layer

BMO-MRW: :

Basal membrane opening minimum rim width

IOP:

Intraocular pressure

sd:

Standard deviation

Aβ:

Amyloid-beta

CSF:

Cerebrospinal fluid

PET:

Positron emission tomography

GCIPL:

Granular cell layer-inner plexiform layer

References

  1. Ge Y-J, Xu W, Ou Y-N, et al. Retinal biomarkers in Alzheimer’s disease and mild cognitive impairment: a systematic review and meta-analysis. Ageing Res Rev. 2021;69: 101361.

    Article  CAS  PubMed  Google Scholar 

  2. Jeevakumar V, Sefton R, Chan J, et al. Association between retinal markers and cognition in older adults: a systematic review. BMJ Open. 2022;12(6): e054657. https://doi.org/10.1136/bmjopen-2021-054657.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Cunha JP, Proenca R, Dias-Santos A, et al. OCT in Alzheimer’s disease: thinning of the RNFL and superior hemiretina. Graefes Arch Clin Exp Ophthalmol. 2017;255:1827–35.

    Article  PubMed  Google Scholar 

  4. Cunha LP, Almeida AL, Costa-Cunha LV, et al. The role of optical coherence tomography in Alzheimer’s disease. Int J Retina Vitreous. 2016;2:24.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Lewis F. Estimation of future cases of dementia from those born in 2015. Consulting report July 2015. Office of Health Economics; 2015.

  6. Liesz A. The vascular side of Alzheimer’s disease. Science. 2019;365:223–4.

    Article  CAS  PubMed  Google Scholar 

  7. Dubois B, Feldman HH, Jacova C, Hampel H, et al. Advancing research diagnostic criteria for Alzheimer’s disease: the IWG-2 criteria. Lancet Neurol. 2014;13:614–29.

    Article  PubMed  Google Scholar 

  8. Sun BL, Li WW, Zhu C, et al. Clinical research on Alzheimer’s disease: progress and perspectives. Neurosci Bull. 2018;34(6):1111–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Viña J, Sanz-Ros J. Alzheimer’s disease: only prevention makes sense. Eur J Clin Invest. 2018;48: e13005.

    Article  PubMed  Google Scholar 

  10. Jansen WJ, Ossenkoppele R, Knol DL, et al. Prevalence of cerebral amyloid pathology in persons without dementia: a meta-analysis. JAMA. 2015;313:1924–38.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Jack CR, Barrio JR, Kepe V. Cerebral amyloid PET imaging in Alzheimer’s disease. Acta Neuropathol. 2013;126:643–57.

    Article  CAS  PubMed  Google Scholar 

  12. Vlassenko AG, Benzinger TLS, Morris JC. PET amyloid-beta imaging in preclinical Alzheimer’s disease. Biochim Biophys Acta. 2012;1822:370–9.

    Article  CAS  PubMed  Google Scholar 

  13. Hornberger J, Bae J, Watson I, et al. Clinical and cost implications of amyloid beta detection with amyloid beta positron emission tomography imaging in early Alzheimer’s disease—the case of florbetapir. Curr Med Res Opin. 2017;33:675–85.

    Article  CAS  PubMed  Google Scholar 

  14. London A, Benhar I, Schwartz M. The retina as a window to the brain-from eye research to CNS disorders. Nat Rev Neurol. 2013;9(1):44–53.

    Article  CAS  PubMed  Google Scholar 

  15. Jindal V. Interconnection between brain and retinal neurodegenerations. Mol Neurobiol. 2015;51(3):885–92.

    Article  CAS  PubMed  Google Scholar 

  16. Den Haan J, Verbraak FD, Visser PJ, et al. Retinal thickness in Alzheimer’s disease: a systematic review and meta-analysis. Alzheimers Dement. 2017;6:162–70.

    Google Scholar 

  17. McGrory S, Cameron JR, Pellegrini E, et al. The application of retinal fundus camera imaging in dementia: a systematic review. Alzheimers Dement. 2017;6:91–107.

    Google Scholar 

  18. Song A, Johnson N, Ayala A, et al. Optical coherence tomography in patients with Alzheimer’s disease: what can it tell us? Eye Brain. 2021;13:1–20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Czako C, Kovacs T, Ungvari Z, et al. Retinal biomarkers for Alzheimer’s disease and vascular cognitive impairment and dementia (VCID): implication for early diagnosis and prognosis. Geroscience. 2020;42:1499–525.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Murueta-Goyena A, Del Pino R, Galdós M, et al. Retinal thickness predicts the risk of cognitive decline in Parkinson disease. Ann Neurol. 2021;89:165–76.

    Article  CAS  PubMed  Google Scholar 

  21. Galvin JE, Kleiman MJ, Walker M. Using optical coherence tomography to screen for cognitive impairment and dementia. J Alzheimers Dis. 2021;84(2):723–36.

    Article  CAS  PubMed  Google Scholar 

  22. Almeida ALM, Pires LA, Figueiredo EA, et al. Correlation between cognitive impairment and retinal neural loss assessed by swept-source optical coherence tomography in patients with mild cognitive impairment. Alzheimers Dement (Amst). 2019;11:659–69.

    Article  PubMed  Google Scholar 

  23. Wu Y, Wang XN, Wang N, et al. Regularity changes of the retinal nerve fiber layer and macular ganglion cell complex in patients with the amnestic mild cognitive impairment. Int J Neurosci. 2018;128:849–53.

    Article  PubMed  Google Scholar 

  24. Girbardt J, Luck T, Kynast J, et al. Reading cognition from the eyes: association of retinal nerve fibre layer thickness with cognitive performance in a population-based study. Brain Commun. 2021;3(4):fcab258.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

No funding was received for this research.

Author information

Authors and Affiliations

Authors

Contributions

SE analyzed and interpreted the patient data regarding the collecting data, applying statistical tests, analyzing data. SA helped to collect patient data. Collecting data. HY was a contributor in analyzing data.

Corresponding author

Correspondence to Sinan Eliaçık.

Ethics declarations

Ethical approval and consent to participate

This study was approved by the Hitit University School of Medicine Ethics Committee (349/06.01.2021) and conducted by following STROBE guidelines for reporting observational studies. The study was approved by the institutional ethics review board and complied with the Declaration of Helsinki. All participants gave their informed consent for this study.

Consent for publication

All authors gave their informed consent for publication of the article. Detailed consent was obtained from each individual participating in the study.

Competing interests

All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Eliaçık, S., Aykaç, S. & Yılmaz, H. Optical coherence tomography findings in children of patients with Alzheimer-type dementia. Egypt J Neurol Psychiatry Neurosurg 59, 98 (2023). https://doi.org/10.1186/s41983-023-00701-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s41983-023-00701-y

Keywords