IMR Press / JIN / Volume 22 / Issue 4 / DOI: 10.31083/j.jin2204106
Open Access Original Research
Lack of Association between CD33 rs3865444 and Amyotrophic Lateral Sclerosis: A Case-Control Study
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1 Department of Neurology, Laboratory of Neurogenetics, University Hospital of Larissa, Faculty of Medicine, University of Thessaly, 41100 Larissa, Greece
2 B’ Department of Neurology, AHEPA University Hospital, Aristotle University of Thessaloniki, 54636 Thessaloniki, Greece
3 Department of Speech and Language Therapy, University of Ioannina, 45110 Ioannina, Greece
4 Neurological Department, Henry Dunant Hospital Center, 11526 Athens, Greece
5 Department of Biomedical Sciences, University of West Attica, 12243 Athens, Greece
6 Department of Medical Imaging, Animus Kyanoys Larisas Hospital, 41222 Larissa, Greece
7 Laboratory of Biochemistry, Faculty of Medicine, University of Thessaly, 41100 Larissa, Greece
8 Department of Rheumatology and Clinical Immunology, University Hospital of Larissa, Faculty of Medicine, University of Thessaly, 41100 Larissa, Greece
9 Department of Neurology, Medical School, University of Cyprus, 1678 Nicosia, Cyprus
*Correspondence: iliampas@uth.gr (Ioannis Liampas)
These authors contributed equally.
J. Integr. Neurosci. 2023, 22(4), 106; https://doi.org/10.31083/j.jin2204106
Submitted: 21 March 2023 | Revised: 26 May 2023 | Accepted: 29 May 2023 | Published: 26 July 2023
Copyright: © 2023 The Author(s). Published by IMR Press.
This is an open access article under the CC BY 4.0 license.
Abstract

Background: Microglial activation is considered to assume a role in the pathogenesis of Amyotrophic Lateral Sclerosis (ALS). To date, the relationship between ALS and the rs3865444 polymorphism of the cluster of differentiation 33 (CD33) has not been explored. The current report aimed to investigate the potential connection between CD33 rs3865444 and ALS. Methods: Patients diagnosed with sporadic ALS according to the revised El Escorial criteria, as well as age and sex matched community controls, were enrolled. Two evenly numbered, age and sex matched groups of 155 participants each were genotyped. Results: No association was found between rs3865444 and ALS [log-additive odds ratio (OR) = 0.83 (0.57, 1.22), over-dominant OR = 0.86 (0.55, 1.36), recessive OR = 0.73 (0.25, 2.17), dominant OR = 0.82 (0.52, 1.29), co-dominant OR1 = 0.68 (0.23, 2.05) and co-dominant OR2 = 0.84 (0.53, 1.33)]. Moreover, no relationship was established between rs3865444 and the age of ALS onset based on both unadjusted and sex adjusted Cox-proportional hazards models. Finally, no association between rs3865444 and ALS was found in subgroup analyses based on the site of ALS onset (bulbar or spinal) and sex. Conclusions: The current analysis is the first to report that rs3865444 is not linked to ALS. Larger multi-racial studies are required to confirm these findings.

Keywords
motor neuron disease
amyotrophic lateral sclerosis
CD33
cluster of differentiation 33
rs3865444
1. Introduction

Amyotrophic lateral sclerosis (ALS) is an inexorable neurodegenerative disorder characterized by concomitant degeneration of upper and lower motor neurons [1]. Typically, ALS initially manifests with focal signs and symptoms that progressively deteriorate and expand to involve additional body regions, but generalized weakness and muscle wasting may be evident from its onset [2]. Cognitive and behavioral disorders may coexist; however, they are not uniformly present [3]. Despite its low worldwide prevalence (about 4–5 cases per 100,000 people) conservative projections predict a forthcoming “growth spurt” that will accompany the constant ageing of the world population [4, 5]. Therefore, ALS devastating nature, along with its ominous epidemiological trajectory increases the urgency for a better understanding of its pathogenesis that will pave the way for advances in its management.

To date, the primary event that instigates the pathophysiological cascade leading to progressive and incessant degeneration of motor neurons remains elusive [6]. Regardless, multiple pathophysiological mechanisms have been implicated in the neurodegenerative processes and are considered to be set in motion by complex interactions among numerous important genetic and environmental factors [7]. In brief, glutamate-mediated excitotoxicity, oxidative (reactive oxygen species) and metabolic (mitochondrial dysfunction) stress, protein misfolding, neurofilament accumulation, formation of intracellular aggregates, disruption of axonal transport and activation of microglia are considered to underlie neurodegenerative processes in ALS [8]. Whether these mechanisms are uniformly implicated in all patients or specific mechanisms, tend to assume predominant roles in distinct subgroups of ALS cases remains to be determined [6, 7].

The cluster of differentiation 33 (CD33) is a transmembrane sialic-acid-binding immunoglobulin-like lectin (siglec) which is principally found on leucocyte subsets and is suspected to regulate immune and inflammatory responses [9, 10]. The CD33 gene is located in chromosome 19p13.33 [11]. CD33 rs3865444 polymorphism constitutes a sequence variant situated within a regulatory region of the CD33 gene that is considered to alternate the expression of CD33, ultimately controlling microglial activation [12]. Its pivotal role in neurodegeneration has been primarily demonstrated by previous studies suggesting a protective effect of the minor allele against the development of Alzheimer’s disease (AD) [13, 14]. Lately, limited research has provided evidence on the protective role of rs3865444 against Parkinson’s disease (PD), as well as its implication in the pathogenesis of multiple sclerosis (MS) [15, 16, 17]. Considering the extensive pathophysiologic and genetic overlap across the spectrum of neurodegeneration, rs3865444 could assume a role in ALS related neurodegeneration, as well [18].

To date, no published article has focused on the relationship between CD33 rs3865444 and ALS. Therefore, the current analysis was undertaken to look into this association. For this purpose, a genetic association study involving individuals diagnosed with ALS and healthy controls of Greek ancestry was performed. The associations between (1) rs3865444 and ALS and (2) rs3865444 and age of disease onset were separately investigated.

2. Materials and Methods
2.1 Participants and Settings

The relationship between CD33 rs3865444 and ALS was explored using a case control design. All procedures were approved by the Institutional Ethics Review Board of the University of Thessaly (59295/23-01-2017) approved the study protocol before its initiation. All participants provided written informed consent prior to participation.

The participant sets of the present study have been previously described [8, 19, 20, 21]. Individuals with ALS were prospectively and consecutively enrolled from the University Neurology Department of the General University Hospital of Larissa. ALS was diagnosed by senior neurologists using the El Escorial diagnostic criteria [22]. Healthy controls were derived from the same community using individual matching (1:1) based on sex and age (± 2 years).

The following prerequisites were considered for the inclusion of patients with ALS: they were above 18 years of age, of Greek ancestry, and diagnosed with sporadic ALS using the revised El Escorial criteria. Candidates with ALS were excluded based on the following: they were diagnosed with any neurodegenerative entity or had a first-degree relative with Motor Neuron Disease (MND) and/or Frontotemporal Dementia (FTD).

The following prerequisites were considered for the inclusion of healthy controls: they were above 18 years of age, of Greek ancestry, and belonged to the same community as the ALS cases. Healthy controls were not considered for enrollment when: they were diagnosed with any neurodegenerative entity or had a first-degree relative with MND and/or FTD.

2.2 DNA Isolation and Genotyping

DNA was isolated from peripheral blood leucocytes via the method of salting out [23, 24]. Primers and probes for the genotyping of CD33 rs3865444, as well as amplification conditions, have been previously described in great detail [17]. Genotyping was performed by applying TaqMan allele-specific discrimination assays using an ABI PRISM 7900 Sequence Detection System (SDS), and analysis of the results was conducted with the SDS software (SDS 2.4, Applied Biosystems, Foster City, CA, USA).

2.3 Statistical Analysis and Outcome Measures

The main focus of the present article was the potential association between CD33 rs3865444 and ALS. A secondary outcome was the investigation of the relationship between the aforementioned single nucleotide polymorphism (SNP) and the age of ALS onset.

Quality assessment was performed by establishing that the group of healthy controls was in Hardy-Weinberg equilibrium (HWE). The power of our sample was determined based on a minor allele frequency (MAF) of 24%, an estimated prevalence of about 5 ALS cases in a 100,000 population, and a relative risk increase of approximately 40% [25]. SNPStats software (https://www.snpstats.net/) was used for the investigation of the association between rs3865444 and ALS [26]. The dominant, recessive, over-dominant, log-additive and co-dominant models of inheritance were assessed. Both unadjusted and age-sex adjusted models were analyzed. Cox proportional hazards models were performed to explore the potential association between rs3865444 and the age of ALS onset, using the SPSS statistical package (version 26.0, IBM Corp., Chicago, IL, USA) Both unadjusted and sex adjusted models were tested.

Moreover, we performed subgroup analyses based on the site of ALS onset by comparing: (1) bulbar onset ALS patients with healthy controls, (2) spinal onset ALS patients with healthy controls and (3) bulbar vs. spinal onset ALS patients. A second subgroup analysis was performed after stratification for sex. For both subgroups analyses, single locus association analyses and cox proportional hazards models were performed as previously described. Both crude and age-sex adjusted analyses were performed (Cox models featured age as the time-to-event variable and were only adjusted for sex, models stratified for sex did not require adjustment for sex).

All analyses were evaluated according to the α = 0.05 threshold of statistical significance.

3. Results
3.1 Sample Characteristics

A group of 155 participants diagnosed with definite sporadic ALS and an evenly numbered group of age-sex matched community controls were formed. The genotype call rate was 99.68%, with genetic data available from 155 patients with ALS and 154 healthy controls. Our sample size possessed a power above 80% to detect a valid association between CD33 rs3865444 and ALS. CD33 rs3865444 followed the HWE principle in the group of healthy participants (p = 0.4). Patient characteristics are displayed in Table 1.

Table 1.Patient characteristics.
Demographics n = 155
Age (mean years ± SD) 63.74 ± 11.30
median (IQR) 65 (57, 72)
Sex (Female/Male) 77/78
Handedness (Right/Left) 136/19
Years of education (6, >6 years) 114/41
Alcohol consumption (Yes/No) 104/51
Smoking (Yes/No) 106/49
Site of disease onset (Spinal/Bulbar/Mixed) 97/50/8

Age is presented in mean ± SD, median (IQR); SD, standard deviation; IQR, interquartile range.

3.2 Genotyping Results

Genotypic and allelic frequencies are illustrated in Table 2. The MAFs were 26% and 23% for the healthy subjects and ALS cases, respectively.

Table 2.Allelic and genotypic frequencies for CD33 rs3865444.
SNP Genotypes/alleles Healthy controls (n = 155) ALS (n = 155) Whole sample (n = 310)
rs3865444 n (%) n (%) n (%)
Genotype C/C 82 (53) 90 (58) 172 (56)
C/A 64 (42) 59 (38) 123 (40)
A/A 8 (5) 6 (4) 14 (5)
Missing data 1 0 1
Allele C 228 (74) 239 (77) 467 (76)
A 80 (26) 71 (23) 151 (24)

SNP, single nucleotide polymorphism; ALS, amyotrophic lateral sclerosis.

The unadjusted analysis did not reveal any relationship between CD33 rs3865444 and ALS (primary outcome measure) regarding any inheritance pattern; log-additive odds ratio (OR) = 0.83 (0.57, 1.22), over-dominant OR = 0.86 (0.55, 1.36), recessive OR = 0.73 (0.25, 2.17), dominant OR = 0.82 (0.52, 1.29), co-dominant OR1 = 0.84 (0.53, 1.33) and co-dominant OR2 = 0.68 (0.23, 2.05) (Table 3). Similarly, age and sex adjusted analyses failed to demonstrate any significant association (Table 3).

Table 3.Single locus unadjusted and age-sex adjusted analysis of the association between CD33 rs3865444 and ALS.
Unadjusted analysis Adjusted analysis
Mode Genotype OR (95% CI) p-value OR (95% CI) p-value
Co-dominant C/C 1.00 0.65 1.00 0.5
C/A 0.84 (0.53–1.33) 0.79 (0.41–1.51)
A/A 0.68 (0.23–2.05) 0.44 (0.09–2.05)
Dominant C/C 1.00 0.39 1.00 0.35
C/A-A/A 0.82 (0.52–1.29) 0.74 (0.40–1.39)
Recessive C/C-C/A 1.00 0.58 1.00 0.35
A/A 0.73 (0.25–2.17) 0.49 (0.11–2.20)
Over-dominant C/C-A/A 1.00 0.53 1.00 0.59
A/C 0.86 (0.55–1.36) 0.84 (0.44–1.58)
Log-additive 0.83 (0.57–1.22) 0.35 0.74 (0.43–1.26) 0.26

ALS, amyotrophic lateral sclerosis; CI, confidence interval; OR, odds ratio.

The association between rs3865444 and the age of ALS onset was additionally explored (Table 4). Neither unadjusted (C/C vs. C/A; hazard ratio (HR) = 0.88 (0.64, 1.23), C/C vs. A/A; HR = 0.72 (0.31, 1.64)) nor sex-adjusted (C/C vs. C/A; HR = 0.84 (0.60, 1.17), C/C vs. A/A; HR = 0.73 (0.32, 1.67)) Cox-proportional hazards models were consistent with no association between the two.

Table 4.Cox regression for the association between CD33 rs3865444 and age of disease onset.
Crude Model Sex-Adjusted Model
Genotype HR (95% CI) p-value HR (95% CI) p-value
C/C Ref NA Ref NA
C/A 0.88 (0.64, 1.23) 0.46 0.84 (0.60, 1.17) 0.30
A/A 0.72 (0.31, 1.64) 0.43 0.73 (0.32, 1.67) 0.46

Ref, reference group; HR, hazard ratio; CI, confidence interval; NA, not applicable.

3.3 Subgroup Analyses
3.3.1 Site of ALS Onset

The unadjusted analysis did not reveal any relationship between CD33 rs3865444 and bulbar onset ALS regarding any inheritance pattern; log-additive OR = 0.79 (0.45, 1.38), over-dominant OR = 0.94 (0.49, 1.80), recessive OR = 0.37 (0.05, 3.05), dominant OR = 0.82 (0.43, 1.57), co-dominant OR1 = 0.88 (0.46, 1.70) and co-dominant OR2 = 0.35 (0.04–2.95) (Table 5). Similarly, the unadjusted analysis did not reveal any relationship between CD33 rs3865444 and spinal onset ALS regarding any inheritance pattern; log-additive OR = 0.88 (0.57, 1.35), over-dominant OR = 0.83 (0.49, 1.40), recessive OR = 0.99 (0.31, 3.12), dominant OR = 0.83 (0.50, 1.39), co-dominant OR1 = 0.82 (0.48–1.40) and co-dominant OR2 = 0.92 (0.28–2.94) (Table 5). Finally, no association was estimated in the comparison between bulbar vs. spinal ALS onset. Similarly, age and sex adjusted analyses failed to demonstrate any significant association (Table 5).

Table 5. Single locus unadjusted and age-sex adjusted analysis of the association between CD33 rs3865444 and bulbar onset ALS.
Bulbar ALS onset vs. healthy controls
Unadjusted analysis Adjusted analysis
Mode Genotype OR (95% CI) p-value OR (95% CI) p-value
Co-dominant C/C 1.00 0.55 1.00 0.11
C/A 0.88 (0.46–1.70) 0.67 (0.25–1.80)
A/A 0.35 (0.04–2.95) 0.09 (0.01–1.08)
Dominant C/C 1.00 0.56 1.00 0.21
C/A-A/A 0.82 (0.43–1.57) 0.55 (0.21–1.43)
Recessive C/C-C/A 1.00 0.3 1.00 0.053
A/A 0.37 (0.05–3.05) 0.10 (0.01–1.22)
Over-dominant C/C-A/A 1.00 0.85 1.00 0.65
A/C 0.94 (0.49–1.80) 0.80 (0.31–2.07)
Log-additive 0.79 (0.45–1.38) 0.4 0.49 (0.21–1.11) 0.082
Spinal ALS onset vs. healthy controls
Unadjusted analysis Adjusted analysis
Mode Genotype OR (95% CI) p-value OR (95% CI) p-value
Co-dominant C/C 1.00 0.77 1.00 0.76
C/A 0.82 (0.48–1.40) 0.82 (0.40–1.68)
A/A 0.92 (0.28–2.94) 0.61 (0.12–3.03)
Dominant C/C 1.00 0.49 1.00 0.52
C/A-A/A 0.83 (0.50–1.39) 0.80 (0.40–1.58)
Recessive C/C-C/A 1.00 0.99 1.00 0.61
A/A 0.99 (0.31–3.12) 0.66 (0.14–3.19)
Over-dominant C/C-A/A 1.00 0.48 1.00 0.67
A/C 0.83 (0.49–1.40) 0.86 (0.43–1.72)
Log-additive 0.88 (0.57–1.35) 0.56 0.81 (0.45–1.44) 0.46
Bulbar ALS onset vs. spinal ALS onset
Unadjusted analysis Adjusted analysis
Mode Genotype OR (95% CI) p-value OR (95% CI) p-value
Co-dominant C/C 1.00 0.61 1.00 0.61
C/A 0.93 (0.46–1.89) 0.99 (0.46–2.13)
A/A 2.59 (0.29–23.21) 2.83 (0.29–27.33)
Dominant C/C 1.00 0.98 1.00 0.84
C/A-A/A 1.01 (0.51–2.02) 1.08 (0.51–2.28)
Recessive C/C-C/A 1.00 0.33 1.00 0.32
A/A 2.66 (0.30–23.44) 2.84 (0.30–26.92)
Over-dominant C/C-A/A 1.00 0.73 1.00 0.85
A/C 0.89 (0.44–1.78) 0.93 (0.44–1.99)
Log-additive 1.11 (0.61–2.02) 0.73 1.18 (0.62–2.25) 0.61

ALS, amyotrophic lateral sclerosis; CI, confidence interval; OR, odds ratio.

In the cox models, no association was found between the rs3865444 and age of ALS onset neither in cases with bulbar (C/C vs. C/A; HR = 0.70 (0.39, 1.27), C/C vs. A/A; HR = 0.34 (0.04, 2.52)) nor in those with spinal onset (C/C vs. C/A; HR = 1.07 (0.70, 1.64), C/C vs. A/A; HR = 0.70 (0.28, 1.76)). Similarly, sex adjusted analyses failed to demonstrate any significant association (Table 6).

Table 6.Subgroup crude cox analysis for the association between CD33 rs3865444 and age of disease onset, based on site of ALS onset.
Bulbar ALS onset
Crude Model Sex-Adjusted Model
Genotype HR (95% CI) p-value HR (95% CI) p-value
C/C Ref NA Ref NA
C/A 0.70 (0.39, 1.27) 0.24 0.59 (0.32, 1.08) 0.09
A/A 0.34 (0.04, 2.52) 0.29 0.34 (0.05, 2.56) 0.29
Spinal ALS onset
Crude Model Sex-Adjusted Model
Genotype HR (95% CI) p-value HR (95% CI) p-value
C/C Ref NA Ref NA
C/A 1.07 (0.70, 1.64) 0.74 1.07 (0.70, 1.64) 0.75
A/A 0.70 (0.28, 1.76) 0.45 0.71 (0.28, 1.79) 0.47

Ref, reference group; HR, hazard ratio; CI, confidence interval; NA, not applicable.

3.3.2 Subgroup Analyses Based on Sex

The unadjusted analysis did not reveal any relationship between CD33 rs3865444 and ALS in male participants regarding any inheritance pattern; log-additive OR = 0.88 (0.51, 1.50), over-dominant OR = 0.92 (0.48, 1.75), recessive OR = 0.75 (0.16, 3.47), dominant OR = 0.87 (0.46, 1.65), co-dominant OR1 = 0.89 (0.47, 1.72) and co-dominant OR2 = 0.72 (0.15, 3.39) (Table 7). Similarly, the unadjusted analysis did not reveal any relationship between CD33 rs3865444 and ALS in female participants regarding any inheritance pattern; log-additive OR = 0.79 (0.46, 1.37), over-dominant OR = 0.81 (0.43, 1.55), recessive OR = 0.72 (0.16, 3.33), dominant OR = 0.77 (0.41, 1.46), co-dominant OR1 = 0.79 (0.41, 1.52) and co-dominant OR2 = 0.65 (0.14–3.08) (Table 7). Similarly, age adjusted analyses failed to demonstrate any significant association (Table 7).

Table 7.Single locus unadjusted and age adjusted analysis of the association between CD33 rs3865444 and ALS stratified by sex.
Subgroup of male participants
Unadjusted analysis Adjusted analysis
Mode Genotype OR (95% CI) p-value OR (95% CI) p-value
Co-dominant C/C 1.00 0.88 1.00 0.71
C/A 0.89 (0.47–1.72) 1.14 (0.47–2.73)
A/A 0.72 (0.15–3.39) 0.45 (0.05–3.94)
Dominant C/C 1.00 0.68 1.00 0.92
C/A-A/A 0.87 (0.46–1.65) 1.04 (0.45–2.43)
Recessive C/C-C/A 1.00 0.71 1.00 0.44
A/A 0.75 (0.16–3.47) 0.43 (0.05–3.64)
Over-dominant C/C-A/A 1.00 0.79 1.00 0.68
A/C 0.92 (0.48–1.75) 1.20 (0.51–2.85)
Log-additive 0.88 (0.51–1.50) 0.63 0.93 (0.45–1.93) 0.85
Subgroup of female participants
Unadjusted analysis Adjusted analysis
Mode Genotype OR (95% CI) p-value OR (95% CI) p-value
Co-dominant C/C 1.00 0.7 1.00 0.32
C/A 0.79 (0.41–1.52) 0.50 (0.19–1.33)
A/A 0.65 (0.14–3.08) 0.41 (0.04–3.84)
Dominant C/C 1.00 0.42 1.00 0.13
C/A-A/A 0.77 (0.41–1.46) 0.49 (0.19–1.27)
Recessive C/C-C/A 1.00 0.67 1.00 0.58
A/A 0.72 (0.16–3.33) 0.54 (0.06–4.82)
Over-dominant C/C-A/A 1.00 0.53 1.00 0.2
A/C 0.81 (0.43–1.55) 0.54 (0.20–1.40)
Log-additive 0.79 (0.46–1.37) 0.4 0.55 (0.25–1.24) 0.14

ALS, amyotrophic lateral sclerosis; CI, confidence interval; OR, odds ratio.

In the cox models, no association was estimated between the rs3865444 and the age of ALS onset neither in the male (C/C vs. C/A; HR = 1.14 (0.72, 1.82), C/C vs. A/A; HR = 0.64 (0.19, 2.06)) nor in the female subgroup (C/C vs. C/A; HR = 0.64 (0.39, 1.02), C/C vs. A/A; HR = 0.93 (0.29, 3.04)). Results can be found in Table 8.

Table 8.Subgroup crude cox analysis for the association between CD33 rs3865444 and age of ALS onset, based on sex.
The subgroup of male participants
Male participants Female participants
Genotype HR (95% CI) p-value HR (95% CI) p-value
C/C Ref NA Ref NA
C/A 1.14 (0.72, 1.82) 0.57 0.64 (0.39, 1.02) 0.06
A/A 0.64 (0.19, 2.06) 0.44 0.93 (0.29, 3.04) 0.91

Ref, reference group; HR, hazard ratio; CI, confidence interval; NA, not applicable.

4. Discussion

The current report was the first to focus on CD33 rs3865444 in patients with ALS and did not establish any associations between the two. Although there is no direct evidence to assess the reproducibility of our results, there is indirect congruent evidence originating from genome-wide association studies (GWASs), which have not revealed a link between rs3865444 and ALS [27, 28]. In rare entities such as ALS, however, the sample size which is required by GWASs to identify SNPs conferring small-sized risks and low-frequency risk-variants may not be feasible to achieve [29]. Of note, although heritability is estimated to explain as much as 50% of the variability of sporadic ALS, the ensemble of risk-loci identified by GWASs occurs in 10% of patients with sporadic ALS [28]. Therefore, the absence of GWAS-based evidence on an association between rs3865444 and ALS is not definitive. In any case, despite the negative results of the present article (and the indirect concurring findings of previous GWASs), additional research is warranted since linkage disequilibrium may vary among ethnic groups, and our findings may not be applicable across individuals with different racial backgrounds.

CD33 rs3865444 polymorphism is considered to alternate the expression of CD33, ultimately controlling microglial activation [12]. To date, most evidence of its implication in neurodegeneration stems from AD research [13, 14]. Relevant studies have shown that individuals with rs3865444 A/A alleles exhibit decreased expression of CD33 in peripheral monocytes and brain tissue compared to those with wild type alleles [30]. Reduced micro-glia expression of CD33 appears to lead to increased phagocytosis of amyloid beta (Aβ) peptide since CD33-lacking microglia phagocytize considerably greater quantities of Aβ peptide [31]. Thus, individuals with minor alleles probably carry a protective effect against the accumulation of Aβ peptide. Although the pathophysiological underpinnings of ALS are heterogeneous from those of AD, microglial activation and neuroinflammation, as well as the balance between homeostatic and deleterious inflammatory processes, appear to be of pivotal importance in the pathogenesis of the disease. The presumed mechanism of CD33 rs3865444 action is presented at Fig. 1.

Fig. 1.

Microglia, the immune cells of the central nervous system, assume a pivotal role in the dynamic regulation of inflammatory responses. Although microglia-mediated inflammation aims at the protection of the brain parenchyma from various insults, the inflammatory milieu might have detrimental effects on the neurons leading to dysfunction and death. Regulatory processes are pivotal in maintaining the balance between inflammatory and homeostatic processes, promoting the resolution of cerebral inflammation and inducing reparatory processes whenever appropriate.

Of note, microglia are speculated to assume a dual role in the pathophysiology of ALS, exhibiting both neurotoxic and neuroprotective properties [32]. Several researchers have even reported the co-existence of detrimental and protective roles in the same disease models [33, 34]. It has been argued that neuroinflammation and microglia activation may assume different roles in the temporal course of ALS or, more intriguingly, that different subsets of ALS cases could demonstrate heterogeneous underlying pathophysiologic mechanisms leading to the common “net outcome” (degeneration of the upper and lower motor neurons) [35]. Based on the aforementioned considerations, it is clear that different patient subsets could exhibit different associations with CD33 rs3865444, as well as other markers of microglial activation. Therefore, current analytic approaches assessing cases with ALS as a whole may fail to detect any association between the two due to systemic bias.

Our study has several limitations. First, despite achieving a power above 80%, there is an almost 20% chance that our analyses failed to detect non-trivial associations between rs3865444 and ALS. More so, there is an even greater probability that the size of our sample was insufficient to reveal truly significant, smaller-sized associations (compared to the relative risk of 1.42 that was used in our power-estimation statistics). Furthermore, study participants originated from a restricted area, geographically located in Central Greece. The formation of such a geographically restricted sample has introduced several advantages by the formation of two comparable participant groups with respect to several unmeasured exposures to numerous environmental factors that may be implicated in ALS (e.g., soil and water metal and pesticide concentrations [36]) but has probably introduced an overmatching bias in genetics. Moreover, our cohort has not been screened for the main genes that have been linked to ALS, such as superoxide dismutase type 1 (SOD1), chromosome 9 open reading frame 72 (C9orf72), Transactive response DNA-binding protein 43 (TDP-43) or fused in sarcoma/translocated in liposarcoma (FUS/TLS) [37, 38]. Finally, the con-duction of larger, cross-ethnic studies is warranted to confirm the extrapolation of our findings in populations with different racial backgrounds.

5. Conclusions

Additional research is required to extract definitive conclusions about the connection between CD33 rs3865444 and ALS, while multinational studies are required to capture differential associations across different racial groups. The meticulous documentation of additional data, along with the imperative transparent reporting of future articles, will unravel potential associations between rs3865444 and other important clinical parameters, such as treatment-response and prognosis.

Availability of Data and Materials

The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.

Author Contributions

VS: Conceptualization, methodology, software, validation, formal analysis, investigation, data curation, writing—original draft preparation, writing—review and editing, supervision. IL: Methodology, software, validation, formal analysis, investigation, data curatimon, writing—original draft preparation, writing—review and editing. AMA, CB, AN, DP, DPB: Validation, investigation, data curation, writing—review and editing. ZT: Software, validation, investigation, data curation, writing—review and editing. GN, EL, PL: Validation, writing—review and editing. GMH: Conceptualization, methodology, resources, writing—review and editing, supervision, project administration. ED: Conceptualization, methodology, resources, writing—review and editing, supervision, project administration, funding acquisition. All authors contributed to editorial changes in the manuscript. All authors read and approved the final manuscript. All authors have participated sufficiently in the work and agreed to be accountable for all aspects of the work.

Ethics Approval and Consent to Participate

All procedures were approved by the Institutional Ethics Review Board of the University of Thessaly (59295/23-01-2017) approved the study protocol before its initiation. All participants provided written informed consent prior to participation.

Acknowledgment

Not applicable.

Funding

This study was supported in part by a research grant from the Research Committee of the University of Thessaly, Greece (code: 5287).

Conflict of Interest

The authors declare no conflict of interest. Vasileios Siokas, Christos Bakirtzis, Efthimios Dardiotis, and Ioannis Liampas are serving as one of the Guest editors of this journal. We declare that Vasileios Siokas, Christos Bakirtzis, Efthimios Dardiotis, and Ioannis Liampas had no involvement in the peer review of this article and has no access to information regarding its peer review. Full responsibility for the editorial process for this article was delegated to Gernot Riedel.

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