Alzheimer’s disease is a slowly progressive cerebral disease that includes preclinical and clinical stages. The preclinical stage usually starts many years before mild cognitive decline occurs. Patients at the preclinical stage are virtually asymptomatic while there are usually measurable changes in the brain, and biomarkers in the cerebrospinal fluid as well as in blood that indicate the earliest signs of the disease .
Although biomarkers in the cerebrospinal fluid are considered more specific, they are only detected through invasive lumbar puncture which has various complications . Blood and neurophysiological imaging could serve as sources for detecting biomarkers through noninvasive methods and at a lower cost.
In the present study, an attempt has been made aiming to evaluate the efficacy of combined noninvasive markers including the score of MNi in BN lymphocytes in peripheral blood as well as digital EEG parameters for early diagnosis of AD.
All patients and controls were subjected to history taking, thorough clinical examination including neuropsychological examination, and MRI to exclude other causes of dementia. Screening for cognitive function has been done using MMSE. The mean score for MMSE was 18.07 ± 4.026 among the AD patients, while for controls the mean score was 28.73 ± 1.443. MMSE score was done for controls to exclude being in early undiagnosed stage of mild cognitive decline, to allow validation of both their EEG results and blood samples as control samples.
The use of EEG has grown prevalent for its capabilities in evaluating cerebral degenerative changes in dementia. Several studies have been directed to deal with EEG changes associated with dementia and to identify its degree of severity . Furthermore, many studies praise the role of EEG as a marker in the early detection of AD [21, 22].
By using conventional EEG in our study, we found normal background activity with no abnormal epileptogenic discharges in both the patient and the control groups. However, digital EEG revealed lower mean absolute power of alpha waves among the patients (6.207 ± 0.3011) compared to the controls (17.21 ± 0.5567). Statistical analysis revealed a highly significant difference between the two groups (P < 0.0001). Mean absolute power of other frequencies was within normal ranges for both patient and control groups. Our study was in agreement with the research study of De Waal et al.  which revealed more EEG abnormalities in AD patients compared to the controls (p < 0.001). Furthermore, Fauzan and Amran  in their study reported a significant reduction in rhythmic alpha frequencies among patients with mild cognitive impairment compared to the controls.
Moreover, Snyder et al.  stated that EEG may have an important role in detecting and classifying dementia regarding its significant influence in terms of rhythm activity that appears in patients with dementia. Micanovic and Pal  as well as Raymundo et al.  emphasized that visual analysis EEG can contribute in diagnosis of AD as it usually reveal power spectrum shifts from high-frequency components (alpha, beta, and gamma) toward low-frequency components (delta and theta).
In the current study, the correlations between cognitive state and the absolute power of alpha wave among the group of patients revealed a positive correlation (r = 0.2235). Although this correlation is considered relatively weak, we suggest that reduced alpha wave power could support the diagnosis when combined with another parameter.
We hypothesized in our study that depending on a single marker reduces the probability of reaching appropriate diagnosis. So, we combined the neurophysiological markers with a genetic marker in a trial to reach reliable findings.
Bajic et al.  clarified that there is an increasing interest in the evaluation of DNA damage markers in individuals liable to develop AD. These biomarkers may identify individuals at early stages of neurodegeneration. This would be useful to allow for appropriate interventions prior to progression of the disease. Moreover, Zivković et al.  declared that genetic instability occurs a number of years prior to clinical diagnosis.
Additionally, Andreassi et al.  emphasized that scoring of the MNi is the most prevalent biomarker for assessing DNA damage in peripheral blood lymphocytes.
Regarding our study, the mean score of MNi among the patients was 10.13 ± 3.420, whereas among controls was 3.167 ± 2.329. Statistical analysis of data revealed a highly significant difference between the two groups (P < 0.0001). These results are consistent to the study done by Trippi et al.  which revealed an increase in the score of MNi in AD patients (P < 0.05), where the mean scores of the patient and control groups were 20.8 ± 9.2 and 9.0 ± 6.8, respectively. Additionally, Petrozzi et al.  revealed a compatible results to our study as they found a statistical significant difference between patients’ mean score of MNi (18.26) versus that of controls (8.56) (P< 0.05).
Our results are in contrast to the study done by Lee et al.  which showed a non-significant difference in the score of MNi among South Australian AD patients compared to controls (P < 0.18). They attributed these results to the environmental diversity between the study population in their research and the previous researches regarding dietary and lifestyle factors . Additionally, the level of MNi in the controls may have already exceeded the threshold of spotting any significant differences compared to AD patients .
By linking scores of both cognitive screening using MMSE and MNi among the patients, our study found a significant negative correlation between the two scores (r = −0.6066). This result is in agreement with Lee et al.  who found a significant negative correlation of r = −0.4 between the two scores among the AD patients group.
Although increased score of MNi can be associated with different disease conditions and cannot be considered specific for AD ; however, the significant correlation between the scores of MNi and MMSE among the patients in our study can augment the prospect of using the MNi as a biomarker for the risk of cognitive decline and for early diagnosis of AD .
Zhang et al.  declared that increase frequency of MNi formation is associated with increased occurrence of chromothripsis. Chromothripsis occurs when a chromosome or a part of a chromosome experiences enormous shattering and consequent reunion of a single chromatid from a micronucleus which can result in accumulated affection of the DNA constitutes within the cells. This can result in a massive acquired genomic rearrangement in a single devastating event . Consequently, this loss of genome integrity may be associated with increased risk for neurodegenerative disease . So, we postulate that this mechanism may underlie the progressive course of AD and consecutive evaluation of the score of MNi for AD patient may help in follow-up. Continued research on micronucleated cells can unravel further unknown pathogenesis of different diseases including cancer and neurodegenerative diseases .
By comparing the association between cognitive state and both MNi scoring (r = −0.6066) and the absolute power of alpha wave (r = 0.2235) among the patients, we found that the MNi scoring is more correlated to the cognitive state which can reflect the distressing effect of genetic damage. This difference between the two correlations may be attributed to the early occurrence of genomic instability than the EEG changes, so at certain level of cognitive impairment genomic instability could be more obvious than the EEG changes. Also, the association between the cognitive state and the EEG changes may become more apparent with increasing the sample size, so subsequent studies with a larger number of AD patients are recommended.
The non-significant correlation between the value of alpha wave power and the MNi scoring among the patients group in our study (r = −0.06844) could also be rationalized by the difference in the course of the two parameters as the genomic instability is suggested to precede the EEG changes.