Season of Birth and Vulnerability to the Pathology of Alzheimer’s Disease: an in Vivo Positron Emission Tomography Study

Abstract

This study used positron emission tomography to examine whether the seasonal birth effect as an exogenic indicator of early life environmental factors influenced vulnerability to Alzheimer’s disease (AD) pathology in the elderly. We analyzed datasets from the Alzheimer’s Disease Neuroimaging Initiative, which included the data for 234 cognitively normal individuals and patients with mild cognitive impairment (n = 115) and AD dementia (n = 38). As an index of amyloid β (Aβ)/tau accumulation, the AV-45/AV-1451-standardized uptake value ratios (SUVRs) were compared between groups of spring-to-summer births and fall-to-winter births by analysis of covariance. Seasonal birth difference was a good predictor of AV-1451 SUVR. We found that participants with a fall-to-winter birth showed lower AV-1451 SUVRs than those with a spring-to-summer birth, after accounting for the Alzheimer’s Disease Assessment Scale-cognitive subscale (ADAS) score and other factors that could possibly affect tau accumulation. Our findings showed a vulnerability to tau pathology in participants with a fall-to-winter birth, which may be caused by perinatal or postnatal brain damage due to the risk factors associated with the cold season.

Introduction

The life-course perspective has been recognized to be important for prevention of dementia ¹, and Barker’s hypothesis of the developmental origins of health and disease (DOHAD) has proposed causative relationships between many chronic diseases in later life and disadvantageous environmental factors during the antenatal and early postnatal periods ².

The season of birth has been suggested to be an exogenic indicator of the environment during early life, and has been shown to be related to an increase in the risk of disadvantageous psychiatric ³ and neurological ⁴ outcomes. The seasonal birth effect has been reported most consistently for schizophrenia, with an excess of births in winter among patients with schizophrenia ⁵. Reports of the seasonal birth effect for patients with dementia are less consistent, with some indicating a deficit of births in spring ⁶ and excess births in winter ⁷ or in the first quarter of the year ⁸ among patients with dementia and Alzheimer's disease (AD), and others failing to find similar associations ^9–11.

Many etiologic hypotheses have been proposed to explain the effect of seasonal birth as a risk factor for disadvantageous psychiatric and neurological outcomes ¹². The most notable hypothesis is that some environmental factors, such as bacterial and viral infections, have a seasonally fluctuating effect and can injure the central nervous system (CNS) of the fetus or the newborn, creating a scar that would permit the development of the disease later in life ¹³. If such an environmental factor, possibly occurring with an intensity that changes depending on the season, could affect the individual brain long before disease development, a seasonal birth effect can be expected for the vulnerability of the brain to AD pathology in later life.

The development of radiotracers that bind to amyloid β (Aβ) and tau has made it possible to examine AD pathology in vivo by positron emission tomography (PET) imaging. However, no previous study has assessed the effect of seasonal birth on AD pathology in vivo. In this study, we examined the seasonal birth effect on the Aβ-tau burden in a sample including cognitively normal (CN) individuals and patients with mild cognitive impairment (MCI) and AD. We aimed to investigate whether the seasonal birth effect as an exogenic indicator of early-life environmental factors affects the vulnerability of the brain to AD pathology in later life.

Results

Demographic characteristics

The demographic characteristics of the birth-season (spring-to-summer and fall-to-winter birth) groups are shown in Table 1. We found no intergroup differences in the ratio of CN/MCI/ AD, age, sex, years of education, and MMSE and ADAS scores.

Comparison of AV-45/AV-1451 SUVR values between groups categorized by season of birth

The cortical AV-45 SUVR showed no significant difference between birth-season groups in ANCOVA with age, sex, years of education, and ADAS score as covariates (Table 2). However, MANCOVA with age, sex, years of education, AV-45 SUVR, and ADAS scores as covariates showed a significant effect of the season of birth on AV-1451 SUVR (F_3,372 = 2.95, p = 0.03). ANCOVA with age, sex, years of education, AV-45 SUVR, and ADAS score as covariates showed significantly larger AV-1451 SUVRs in areas corresponding to Braak stages 1&2 and 3&4 in the group of spring-to-summer births (Table 2).

Multiple regression analysis predicting regional AV-1451 SUVRs

We found that the seasonal birth difference was a good predictor of AV-1451 SUVR in areas corresponding to Braak stages 1&2 and 3&4 with multiple regression analysis predicting regional AV-1451 SUVR (Table 3). The results of the hierarchical regression analyses are presented in Table 4. Seasonal birth, added in the final step, accounted for a significant increase in the variance of AV-1451 SUVR values in areas corresponding to Braak stages 1&2 and 3&4 after controlling for age, sex, years of education, ADAS score, and AV-45 SUVR.

Discussion

To our knowledge, the present study is the first to assess the seasonal birth effect on AD pathology as a proxy for an exogenic indicator of early life environment with a relevant sample size of participants using in vivo PET imaging. The seasonal birth difference was a good predictor of tau accumulation after accounting for age, sex, years of education, Aβ aggregation, and ADAS score. We found that participants with a fall-to-winter birth showed less tau accumulation than those with a spring-to-summer birth after accounting for the cognitive score and other factors that may influence tau accumulation. These findings indicate a vulnerability of participants with a fall-to-winter birth against the accumulation of tau-related pathological damage. In our sample, there was no significant seasonal birth effect on the vulnerability to Aβ aggregation. The lower strength of the association of Aβ with seasonal birth may result from a more proximal association of tau with cognitive dysfunction ^14,15. The finding of a significant seasonal birth effect on the vulnerability to tau pathology in the elderly is consistent with the etiological studies reporting a deficit of spring-births ⁶ or excess births in winter ⁷ or the first quarter of the year ⁸ among patients with dementia and Alzheimer's disease.

Previous studies have tried to reveal how some individuals maintain normal cognitive performance despite the aggregation of AD pathology ^16,17, thus decreasing the risk of onset or delaying the emergence of symptomatic AD ^18,19. The cognitive reserve (CR) presumes individual differences in neural networks or cognitive processes that make it possible for some individuals to cope better than others with brain damage ¹⁹. A higher CR has been proposed to compensate for neurodegenerative damage: participants with a high CR cope better with the onset of dementia, and are able to preserve a normal cognitive level for a longer time than those with low CR ^18,20,21. Furthermore, AD patients with high CR should have more advanced AD pathology to reveal the same level of cognitive dysfunction as those with low CR ¹⁷. Our findings of vulnerability to accumulation of tau pathological damage in participants with a fall-to-winter birth are consistent with the CR theory, indicating a lower CR in fall-to-winter-born elderly when compared to those born in spring to summer.

Although the underlying causes of the vulnerability to tau accumulation in participants with a fall-to-winter birth are still unclear, some seasonally fluctuating risk factors may influence this finding. In studies on the seasonal birth effect on the risk of disease, the findings have been the most consistent for schizophrenia, with a significant excess of births in winter, and it has been suggested that winter-born infants have a greater chance of disadvantageous environmental or obstetrical complications ²², extreme temperature ²³, or seasonal variations in nutritional practices ²⁴. The most reasonable hypothesis, however, is that winter-born infants are more likely to be exposed to perinatal bacterial and viral infections, which may harm the brain and promote the appearance of functional psychosis in those at risk genetically ^25–27.

In accordance with the hypothesized seasonal birth effect on brain damage in schizophrenia, winter-born schizophrenic patients were reported to have lower levels of skin conductance and fewer skin conductance responses ²⁸, and it has been suggested that a bacterial or viral infection, or some other winter-birth-related perinatal complication, causes brain damage leading to dysregulation of electrodermal activity. Analogous to this hypothesized brain damage in winter-born schizophrenic patients, the vulnerability of the fall-to-winter-born elderly against AD pathology may be caused by brain damage due to risk factors associated with fall-to-winter births. The cold climate could make pregnant women or newborns more likely to be exposed to infectious diseases or other noxious agents. As a result, fall-to-winter-born individuals would be at a higher risk of developing cognitive deficits or showing more severe symptoms due to AD pathology.

Our study had some limitations. First, only cross-sectional datasets were analyzed in this study, and we could not examine the direct causality between seasonal birth and the longitudinal progress of AD pathology. Second, despite a recent report showing a modifying effect of environmental factors on AD pathology, especially in apolipoprotein E (ApoE) ε4 carriers ²⁹, we could not examine the effect of the ApoE genotype on the seasonal birth effect on AD pathology because genotyping was not carried out in our entire sample.

In summary, we found that participants with a fall-to-winter birth showed less tau accumulation than those with a spring-to-summer birth after accounting for the cognitive score and other factors that may affect tau accumulation. Our findings showed a lower CR in participants with a fall-to-winter birth, indicating vulnerability to the accumulation of tau pathological damage in these participants. It is possible that low ambient temperatures in cold seasons could increase the exposure of pregnant women or newborns to infectious diseases or other noxious agents, which may cause brain damage to the fetus or newborn, leading to vulnerabilities against accumulation of tau in later life. Further cohort studies are necessary to verify this hypothesis.

Methods

We obtained and used data from the ADNI database (http://adni.loni.usc.edu) for the preparation of this article. The ADNI was launched in 2003 as a public–private partnership led by Principal Investigator Michael W. Weiner, MD. The primary goal of ADNI is to test whether serial magnetic resonance imaging (MRI), PET, other biological markers, and clinical and neuropsychological assessments can be combined to measure the progression of MCI and early AD. For up-to-date information, see http://www.adni-info.org. This study was approved by the Research Ethics Committee of National Center for Geriatrics and Gerontology. We confirm that all methods were performed in accordance with the relevant guidelines and regulations.

Participants

In this study, we included patients diagnosed with MCI or AD as well as CN participants. The inclusion criteria were as follows: for CN, Mini-Mental State Examination (MMSE) scores between 24 and 30 and non-depressed, non-MCI, and non-demented status; for participants with MCI, MMSE scores between 24 and 30, objective memory loss evidenced by education-adjusted scores on the Wechsler Memory Scale Logical Memory II, a Clinical Dementia Rating (CDR) of 0.5, lack of significant levels of impairment in other cognitive domains, essentially preserved activities of daily living, and an absence of dementia; and for participants with AD, MMSE scores between 20 and 26 and meeting the National Institute of Neurological and Communicative Disorders and Stroke & the Alzheimer's Disease and Related Disorders Association criteria for probable AD ³⁰.

ADNI-3 data were obtained from participants aged 55 through 95 years who underwent both AV-45 and AV-1451 scans. The participants also completed a neuropsychological assessment. Data from 387 participants were eventually used in this study, including 234 CN participants and 153 patients diagnosed with MCI (n = 115) or AD dementia (n = 38). We extracted general participant information (age, sex, years of education, MMSE score, and Alzheimer’s Disease Assessment Scale-cognitive subscale-11 [ADAS] score) from the ADNI databases.

Aβ and tau PET analysis

We analyzed ¹⁸F-AV45 and ¹⁸F-AV-1451 imaging data from ADNI-3 as of January 15, 2021. The protocol for acquisition and image preprocessing of these data is publicly available on the ADNI website (http://adni.loni.usc.edu/).

In the dataset, mean AV-45 uptake was shown in the cortical gray matter regions of interest (ROIs) for all participants. The ROIs included the bilateral frontal, lateral temporal, and lateral parietal and anterior/posterior cingulate cortices, as defined by the ADNI group. ROI-based AV-45 standardized uptake value ratios (SUVRs) were calculated with reference to the mean AV-45 uptake of the whole cerebellum. The details of the data-processing method are shown in “UC Berkeley- AV45 Analysis Methods (PDF)” (https://ida.loni.usc.edu/pages/access/studyData.jsp).

For the AV-1451 dataset, tracer retention was quantified in ROIs that anatomically approximated the pathological stages of tangle deposition delineated by Braak and Braak ³¹. Weighted mean SUVR was calculated from three composite ROIs that corresponded to the anatomical definitions of Braak stages 1 & 2 (transentorhinal), 3 & 4 (medial temporal and limbic), and 5 & 6 (neocortical) with reference to the mean AV-1451 uptake of the inferior cerebellum. The details of the data-processing method are shown in “UC Berkeley-Flortaucipir (AV-1451) processing methods (PDF)” (https://ida.loni.usc.edu/pages/access/studyData.jsp).

Statistics

Differences in demographic characteristics between the spring-to-summer (from March to August) and fall-to-winter (from September to February) birth groups were examined using t-tests for continuous variables and χ² tests for dichotomous variables.

The mean SUVR values of AV-45 from composite ROIs of cortical gray matter regions as an index of regional Aβ were compared between groups of spring-to-summer and fall-to-winter birth groups with analysis of covariance (ANCOVA) using age, sex, years of education, and ADAS score as covariates.

The mean SUVR values of AV-1451 from composite ROIs as an index of tau accumulation in regions corresponding to Braak stages 1 & 2, 3 & 4, and 5 & 6 were compared between the spring-to-summer and fall-to-winter birth groups using multiple analysis of covariance (MANCOVA) with age, sex, years of education, AV-45 SUVR, and ADAS score as covariates. Follow-up ANCOVA was performed to examine the group differences in AV-1451 SUVRs in each region with age, sex, years of education, mean SUVR value of AV-45, and ADAS score as covariates.

In addition, a multiple linear regression analysis was performed to determine whether the season of birth was a predictor of AV-45 and/or AV-1451 SUVR, for which a difference was shown in the above-mentioned analysis. The dependent variables were the AV-45 and/or AV-1451 SUVRs, and the independent variables were the season of birth (spring-to-summer vs. fall-to-winter birth), age, sex, years of education, AV45 SUVR (only in the analysis of AV-1451 as the dependent variable), and ADAS score. To examine the effect of seasonal birth on the regional AV-45 and/or AV-1451 SUVR, hierarchical regression equations with steps of predictor variables were fitted. Scores for the measures of age, sex, years of education, AV-45 SUVR (only in the analysis of AV-1451 as the dependent variable), and ADAS score were added in the first step to control for other predictor variables. The birth season was included in the final step.

SPSS for Windows 26.0 (IBM Japan, Tokyo, Japan) was used for statistical analysis. Statistical tests were two-tailed, and significance was defined as a p-value less than 0.05/n using the Bonferroni correction (where n refers to the number of multiple comparisons).

Declarations

Acknowledgments

The authors would like to thank the ADNI participants and study sites for their contributions to the study. The authors have no disclosures to report. Data collection and sharing for this project were funded by the Alzheimer’s Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following donors: AbbVie; Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd. and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research provides funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (http://www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer’s Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California.

This research was supported by the Research Funding for Longevity Sciences (19-11) (21-31) from the National Center for Geriatrics and Gerontology and Grants-in-Aid for Scientific Research (B) 19H03590, from the Japan Society for the Promotion of Science.

Author contributions

F.Y. and H.M. conceived the study. F.Y. and H.M. conducted the features extraction from the raw data sources and validation. F.Y. implemented the data analysis framework and analyzed the results. All authors reviewed the manuscript.

Competing interests

The authors declare no competing interests.

Data availability statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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