Obesity is associated with many chronic diseases including cortisol rhythm disorder and low testosterone. Furthermore, studies on obese children are quite limited and no concordance results have been obtained, especially for boys in puberty. Moreover, the sample sizes of previous studies were small, and were not representative.We conducted a cross-sectional survey including 1148 boys aged 6–14 years, they were divided into overweight/obesity (OW/OB) group and normal weight (NW) group. Puberty status was assessed according to Tanner scale and testicular volume. Serum levels of pregnenolone, 17-OH progesterone, corticosterone, dehydroepiandrosterone (DHEA), and androstenedione were detected by LC-MS. Serum free testosterone and sex hormone-binding globulin (SHBG) levels were measured by chemiluminescence immunoassay.P values were < 0.01). Furthermore, androstenedione and free testosterone levels were lower in OW/OB boys at late puberty, and the trend continued at the post pubertal stage for FT (P < 0.01–0.05). DHEA, androstenedione, and FT levels persisted to be higher at the 10~ < 12 years in OW/OB boys but not for 17-OH progesterone. FT level was lower in the OW/OB group at the 12~ < 15 years group. The SHBG levels in the OW/OB boys were lower than those in the NW ones at the 6~12 years group, and prepubertal to early pubertal stage.The 17-OH progesterone, DHEA, androstenedione and free testosterone levels of OW/OB boys at prepubertal stage or at the age 6 = < 10 years group were higher than those of the NW boys (all the Premature adrenarche is more likely in OW/OB boys. More attention should be given to the lower androgen levels of OW/OB boys at late pubertal and post pubertal stages. Obesity is associated with many chronic disorders such as anxiety, depression, high blood pressure, hyperlipidemia, type 2 diabetes mellitus, obstructive sleep apnea, certain types of cancer, osteoarthritis, and asthma –3. LowerLimited studies have been performed on steroid hormones in OB children, and no concordance results have been obtained to date, studies on steroid levels in OB children have shown that TT levels in prepubertal OB boys were higher than , 11, or It was a cross-sectional survey conducted in Shunyi District, Beijing, 3 elementary schools and 3 middle schools were selected by the cluster sampling method. A total of 1220 Chinese boys aged 6 to 14 years took part in the study, and 72 boys (5.90%) with history of hypogonadism, primary hyperlipidemia, hypertension, diabetes mellitus, impaired fasting glucose, impaired glucose tolerance, syndromic or endocrine obesity, or those undergoing pharmacological treatment were excluded. At last, total 1148 (94.10%) boys completed the survey. The heights, weights, waist circumferences (WC) and hip circumferences of male students were recorded. The puberty staging was performed using the Tanner scale (refer to the methods below). This study was authorized by the Ethics Committee of Beijing Children’s Hospital affiliated to Capital Medical University . All parents of the enrolled children in this study were informed and provided a signed a consent to provide the data for this study. All the boys were divided into three age groups, 6~ < 10 years, 10~ < 12 years, 12~ < 15 years.The pubertal stage assignment and testicular volume estimation were performed by well-trained pediatric endocrinology specialist using a Prader orchidometer. Subjects were classified according to their testicular volume and pubic hair for Tanner stages. The puberty stages were assessed as follows: boys with testicular volume of 3 ml or less were considered prepuberty, 4~8 ml were considered early puberty, > 8-15 ml were considered mid puberty, > 15-20 ml were considered late puberty, 20–25 ml were considered post puberty. Pubic hair stages (PH1–PH5) were recorded according to Tanner .Students were divided into two groups, according to their body mass index (BMI): OW/OB group, and NW group . BMI wasThe serum samples were acquired using a protocol as described previously for determining the concentrations of steroid hormones . The LC-P < 0.05 was considered statistically significant.The SAS JMP  was used for data analyses. Normality was checked using Shapiro-Wilk tests. The anthropometric data and hormonal data were not normally distributed. Non-normal distribution data were expressed as (25th–75th percentiles). Differences between groups were determined using the Wilcoxon’s non-parametric test. Hormonal parameters pregnenolone, 17-OH progesterone, corticosterone, DHEA, androstenedione, SHBG and FT underwent a logarithmic transformation to enhance normality, linear regression analysis was used to test the effect of BMI-SDS, WC-height ratio on the above steroid hormones in prepubertal boys and those having a testis volume > 3 ml together. The general information of the enrolled 1148 boys is listed in Table P < 0.01). The 17-OH progesterone levels in the OW/OB group at the early puberty to post puberty phases were not different compared to the NW groups. However, the level at the prepuberty phase was notably higher than that in the NW group .The DHEA, androstenedione, and FT levels in the OW/OB group were significantly higher than in the NW group at the prepuberty phase . The androstenedione and FT levels in the OW/OB group were lower than those in the NW group at the late puberty phase . The FT levels of the OW/OB boys were lower than those in the NW group, as well as in the post puberty phase . The corticosterone levels of OW/OB boys did not show any significant alteration compared to those in the NW group at all pubertal stages. Serum SHBG levels were measured in 344 boys, which showed a gradual decline along with the development of puberty in NW boys. Due to the limited sample size, the SHBG levels between the OW/OB and NW groups at the prepuberty, early puberty and mid puberty phases were compared, which revealed that the SHBG of OW/OB boys were obviously lower than those in the NW group .The serum levels of pregnenolone, corticosterone, 17-OH progesterone, DHEA, androstenedione, and FT in the NW and OW/OB groups at different pubertal stages were measured, and the results are listed in Table The comparisons of steroid hormones between OW/OB groups and NW groups in different pubic hair staging were shown in Additional file The serum levels of 17-OH progesterone, DHEA, androstenedione, and FT in the OW/OB groups were higher than those in the NW groups at the 6~ < 10 years group, DHEA, androstenedione, and FT persisted higher at the 10~ < 12 years but not for 17-OH progesterone. However, the pregnenolone level in OW/OB group was lower than in NW group at the same age group. FT showed lower in the OW/OB group at the 12~ < 15 years group. The SHBG level in the OW/OB group was lower in the NW group at the both 6~ < 10 years and 10~ < 12 years group.P < 0 .01), DHEA , androstenedione  and FT  levels, however, BMI SDS was a negative predictor of SHBG  level. In all boys with testis volume > 3 ml, BMI-SDS was a negative predictor of pregnenolone , FT , SHBG  levels. However, no association between BMI SDS and 17-OH progesterone, DHEA, androstenedione was found. All results remained unchanged when BMI SDS was substituted by WC to height ratio in the analyses (data were not shown).In prepubertal boys, BMI-SDS was a positive predictor of 17-OH progesterone , fasciculate zone (17-OH progesterone), and reticular zone hormones  by comparing 6–14 year-old OW/OB boys to NW ones. These results revealed that the serum pregnenolone and corticosterone levels of NW boys did not reveal a significant change during pubertal development. However, 17-OH progesterone, DHEA, androstenedione and FT progressively increased with puberty development. The serum levels of 17-OH progesterone from fasciculate zone, DHEA, androstenedione and FT from the reticular zone in OW/OB boys were higher than those in NW boys at prepuberty or aged 6~10 years, in which the alteration was closely correlated with body mass index and WC/height. The result of increasing FT levels in OW/OB boys at prepuberty stage is consistent with the findings of Vandewalle and Reinehr , 17. It 17-OH progesterone is an intermediate product from the corticosteroid cortisol synthetic process. Our data revealed that the serum level of 17-OH progesterone in OW/OB boys increased at prepuberty and aged 6~10 years. However, Reinehr et al.  reportedIn the present study, corticosterone, mineralocorticoid precursors, dose not exhibit an obvious change. In addition, Reinehr et al.  found thFurthermore, in the present study, we found that serum FT level was lower in OW/OB boys than NW boys at the late puberty and post puberty stage, which was consistent with the results of Vandewalle (in mature obese adolescents) and Mogri  , 15. AndThe present study revealed that BMI was negatively related to FT among boys having testis volume > 3 ml. Previous studies have concluded that BMI, waist circumference and estrogen levels were the negative feedback regulation by LH, and the greater the degree of obesity, the more obvious the negative feedback regulation became , 31. In In conclusion, our study revealed that the adrenal androgens DHEA and androstenedione are increased in prepubertal obese vs NW boys, consistent with the known increase in the frequency of premature adrenarche in obese children. In addition, more attention should be given to the lower androgen levels of OW/OB boys at late pubertal and post pubertal stages. The characteristics of the present study are as follows: (1) The study population was a cross-sectional survey of primary and secondary school students, which is different from the previous study that focused on hospital-visiting populations or participants in a weight losing program of OB children. Our study represents the true distribution of the normal and general populations. (2) More population was enrolled into the present study, especially for pre-adolescent and early adolescent children. (3) Most of the hormones were analyzed using a sensitive and specific method, LC-MS, except for FT and SHBG. (4) This study is the first to explore the alteration of adrenal glucocorticoid and mineralocorticoid precursors in OB children at different stages of adolescence. (5) The adolescent stages of the boys were classified more scientifically. On the other hand, the weak points of this study were as follows: (1) The serum cortisol and aldosterone levels were not detected in this study. (2) The sample size of children at adolescent maturity is not enough.Additional file 1: Table S1. Serum adrenal steroid levels in both the NW and OW/OB groups at different Tanner genital stages.


Here, we used a well-validated automated MR segmentation protocol to measure hippocampal subfield volumes in 436 non-demented adults aged 50+. We explored relationships between hippocampal subfield volume and verbal episodic memory, as indexed by word list recall at immediate presentation and following delay. In separate multilevel models for each task, we tested linearity and non-linearity of associations between recall performance and subfield volume. Fully-adjusted models revealed that immediate and delayed recall were both associated with cubic fits with respect to volume of subfields CA1, CA2/3, CA4, molecular layer, and granule cell layer of dentate gyrus; moreover, these effects were partly dissociable from quadratic age trends, observed for subiculum, molecular layer, hippocampal tail, and CA1. Furthermore, analyses of semantic fluency data revealed little evidence of robust associations with hippocampal subfield volumes. Our results show that specific hippocampal subfields manifest associations with memory encoding and retrieval performance in non-demented older adults; these effects are partly dissociable from age-related atrophy, and from retrieval of well-consolidated semantic categories.The heterogeneous specialisation of hippocampal subfields across memory functions has been widely shown in animal models. Yet, few  Decades of ex vivo human studies and in vivo animal studies have revealed anatomical and functional heterogeneity of the hippocampal subfields12. Yet, until recently, very few in vivo studies in humans had shown dissociable relationships between performance in different memory domains and hippocampal subfield anatomy or function15.Hippocampus is among the most important brain structures involved in memory16. Yet, despite this, there remains a limited understanding of the role of hippocampal subfields in other memory domains relied on in daily life, such as verbal episodic memory  or semantic memory  [but see17]. Verbal episodic and semantic memory have been shown to dissociate to hippocampal versus anterior temporal regions respectively22. However, much of our understanding of these dissociations is based on small and heterogeneous patient cohorts21. Little is known about these relationships in the context of healthy ageing; less still is known about the effects of age with respect to relationships between hippocampal subfields and specific memory domains, despite evidence of age-related variation in subfield anatomy25.The role of the hippocampal subfields with respect to select domains of memory thus remains under explored. Recent work has shown that errors during real-world spatial navigation are negatively associated with hippocampal tail volume in mild cognitive impairment (MCI), but with Cornu Ammonis (CA) 3 volume in healthy controlsin vivo datasets29. Spatially refined subfield parcellations have now been used in studies of clinical disorders31, and in one study of MCI and educational attainment32. Nevertheless, a pressing concern is the quantification of relationships between hippocampal subfields, memory domains, and age, particularly given projected worldwide growth in dementia prevalence in older adults33, and the key role of hippocampus in modulating memory34.Recent advances in computational methods and atlases available for anatomical MRI have improved the reliability and efficiency with which histologically-validated hippocampal parcellations may be applied to 35. In contrast, we expected that fluency in semantic memory  would show little if any relationship with subfield volumes19. We appraised these relationships in tandem with age-related differences in subfield volumes, by assessing the robustness of effects related to memory alongside fits for cross-sectional age.Here, we explored the role of hippocampal subfield anatomy with respect to two domains of memory, in healthy ageing. In a large, non-demented sample of community-dwelling older adults, we aimed to dissociate memory domains based on their expected patterning with hippocampal subfield volumes. We predicted relationships would emerge between verbal episodic memory  and volumes of subfields CA1, CA2/3, CA4, and granule cell layer of dentate gyrus (GC-DG) – regions heavily implicated in encoding and retrieval processes37. Briefly, the study comprises a clustered stratified random sample of the population aged 50 and over living in the Republic of Ireland. At Wave 3 (2014), participants completed a computer assisted personal interview in their home , and a physical health assessment with a trained research nurse at a health centre, or at home . Wave 3 participants who completed a health assessment were later invited to complete the MRI protocol. The study received ethical approval from the Research Ethics Committee, School of Medicine, Trinity College Dublin. All experimental procedures were performed in line with Trinity College Dublin School of Medicine guidelines and regulations for ethics in research involving human participants.Details of TILDA’s design have been published previouslyInitial recruitment prioritised participants aged 65 and over in order to limit attrition amongst the oldest old within the sample, with later recruitment targeting those aged 50–64 years. Participants provided voluntary informed consent before their scan appointment.1w datasets were acquired from 560 participants; 18 did not provide data . Supplementary Fig. In total, 578 participants attended for MRI. TParticipants’ verbal episodic memory and semantic fluency performance were assessed by trained interviewers during the Wave 3 CAPI. Assessments comprised immediate and delayed verbal recall of word lists; semantic fluency was assessed by free naming of animals. All participants were fluent English speakers.38; see Supplementary Methods). The list was then presented to the participant by audio recording, or by the interviewer reading aloud . Participants were instructed to listen to the entire list carefully (approx. rate: 1 word/2 s), and were then prompted to repeat as many of the presented words as possible within two minutes. The interviewer recorded the number of words recalled correctly. The test was then repeated at once using the same procedure. The participant’s IR score was calculated as the mean number of words recalled correctly across the first and second attempt. The CAPI then proceeded to the animal naming task (see below), followed by five further sections of questions . Following this, participants completed the DR test, which required them to repeat as many of the word list items from the IR test as possible; DR score was the number of words recalled correctly. IR and DR were weakly negatively correlated with age , and highly positively correlated with each other .IR and DR were tested during the cognitive module in the CAPI. One of four possible 10-item word lists was selected randomly by the CAPI computer , and weakly positively correlated with IR and DR .Participants were instructed to name as many animals as possible in 60 seconds. Task timing was controlled by the CAPI computer. The interviewer recorded each word spoken by the participant, scoring as correct common nouns , and as incorrect any repeated items or proper nouns. AN was weakly negatively correlated with age , St. James’ Hospital, Dublin, via 3 T Philip’s Achieva system with 32-channel head coil. A 3D Magnetisation-prepared Rapid Gradient Echo (MP-RAGE) sequence was used. FOV (mm): 240 × 218 × 162; 0.9 mm isotropic resolution; SENSE factor: 2; TR: 6.7 ms; TE: 3.1 ms; flip angle: 9°.1w image analyses were completed in FreeSurfer v.6.041. We used the hippocampal subfields module within the FreeSurfer recon-all processing pipeline to segment hippocampus39. Details of these hippocampal segmentation routines have been published previously26. Briefly, the procedure employs a probabilistic atlas encoded in a tetrahedral mesh, and derived from manual segmentations using Bayesian techniques. Segmentation is posed as a Bayesian inference problem within a generative model, which spatially deforms atlas label prior probabilities; segmentations are achieved via Bayesian optimisation, based on the label prior probabilities and observed voxel intensities  for hippocampal subfields per participant were gathered using FreeSurfer routines . Data were analysed in STATA 14 .Hemisphere-wise volumetric data , smoker status , handedness, and cardiovascular disease  as fixed effect covariates. Frailty variables were included with the other covariates in initial models, but were dropped due to lack of improvement in model fit when entered in isolation or together . Covariates were selected based on previous literature showing impacts of cardiovascular risk42, smoking43, education32, and frailty44 on tissue volumes.The tightly folded structure of hippocampus leads to high correlation of subfield volumes within and between hemispheres; in part, this may arise via limitations with In separate models, we tested effects of IR, DR, and AN as predictors of hippocampal subfield volumes. Tasks were modelled separately to avoid multicollinearity. Initial inspection of data suggested non-linear trends between recall performance and subfield volumes. We therefore modelled linear, quadratic, and cubic terms for recall tasks, appraising model fit relative to the next simplest alternative using likelihood ratio tests. Models specified subfield as a fixed term, in addition to subfield being nested in the hemisphere random effect. We hypothesised that subfields including CA1, CA2/3, CA4 and GC-DG would be critical to learning performance, and therefore specified fixed effect linear and non-linear interaction terms between IR/DR and subfield. To explore effects of age comprehensively, we further included fixed effect linear and quadratic interaction terms between age and subfield. Within-model statistical significance (α = 0.05) of all terms was evaluated using Wald tests. All non-linear terms were evaluated with respect to the significance of the related lower order terms; e.g., in the case of quadratic terms, we deemed as significant only those where the corresponding linear term was also significant (since the interpretation of a significant quadratic term in isolation was not meaningful within the present models).To evaluate the stability of final mixed effect fits for recall tasks, we performed 10-fold cross validation. We used a random sampling procedure to divide the cohort into 10 folds of approximately equal size ; we then iteratively fitted the fully-adjusted mixed models to 90% of the data, holding the remaining 10% for validation. Initial models of 90% of the data were estimated using fixed and random effects; predictions for the held-out 10% sample used the fixed model terms only. Root-mean-square error (RMSE) values were calculated for each of the 10 sets of predictions.Using mixed effects linear regression, we analysed hippocampal subfield volumes with respect to recall performance. Figure χ2(11) = 555.6, p < 0.00001) and linear (LR: χ2(22) = 565.8, p < 0.00001) IR and their subfield interaction terms in the model. Cubic IR terms and their interaction with subfield significantly improved the fit of the fully adjusted model, relative to the fully adjusted model with no IR terms (LR: χ2(33) = 611.0, p < 0.00001; ΔAIC: 547). Similarly, in the fully adjusted DR model, the cubic DR and subfield interaction terms improved the fit significantly, compared to the quadratic (LR: χ2(11) = 552.0, p < 0.00001) and linear only (LR: χ2(22) = 576.95, p < 0.00001) DR and subfield interaction terms; the fully adjusted model with cubic DR terms significantly improved the fit relative to that model omitting all DR terms (LR: χ2(33) = 613.02, p < 0.00001; ΔAIC: 547).We appraised whether inclusion of IR terms and their subfield interactions improved model fit. Iterative addition of IR interaction terms to the fully adjusted model revealed that the cubic IR terms and their interaction with subfield significantly improved the model fit, over quadratic (likelihood ratio [LR] test: p < 0.006), CA2/3 (p < 0.001), CA4 (p < 0.01), GC-DG (p < 0.007), and molecular layer (p < 0.008) , CA1 (p < 0.005), molecular layer (p < 0.0001), and hippocampal tail (p < 0.0001), with a marginal trend for GC-DG , GC-DG (p < 0.023), and molecular layer (p < 0.016), with a marginally significant cubic term for CA4 (p < 0.065); the cubic term did not reach significance for CA2/3 (p > 0.1), but the quadratic term was significant (p < 0.029) , molecular layer (p < 0.001), hippocampal tail (p < 0.0001), with a weak trend for CA1 . Evaluating the AN model against the fully adjusted model with no AN interaction terms showed no significant improvement in model fit with the addition of the AN terms (LR: LR: χ2(11) = −489.0, p > 0.9; ΔAIC: −511). Quadratic age effects in the model including AN terms recapitulated the IR model, with age effects at presubiculum and fimbria also reaching significance; however, omitting the AN terms yielded age effects consistent with the IR model . As for the IR and DR models, we fitted the interaction between AN and subfield to the fully adjusted model. The subfield x AN linear interaction reached significance for presubiculum only  performance during verbal list learning was associated non-linearly with volumes of CA1, CA2/3, CA4, GC-DG, and molecular layer, with cubic terms providing the best fits per subfield. Similarly, subsequent performance on list delayed recall (DR) was associated non-linearly with volumes of these subfields; again, cubic terms tended to afford the best fits (cf. CA2/3). In parallel, we observed age-related decline in the volumes of subiculum, molecular layer, and hippocampal tail in both models, with further declines noted for CA1 and GC-DG in the IR model; age-related declines were best fit by quadratic terms. Finally, we found that semantic fluency was not robustly associated with volumes of hippocampal subfields.45, and CA146, subiculum47, and presubiculum45 in delayed verbal recall. Our current IR findings implicate each of the CA subfields and GC-DG, supporting their previously demonstrated roles in encoding of novel stimuli/environments34, and in verbal and visuo-spatial episodic memory48. Our DR results agree in part with the IR findings; although cubic fit robustness was reduced for CA2/3 and CA4, overall trends showed that DR performance fluctuated non-linearly with CA, GC-DG and molecular layer subfield volume (further to17). Augmenting these results, our observation that free recall of familiar semantic categories showed little relationship with subfield volumes agrees with accounts of semantic memory as dissociable to non-hippocampal medial temporal regions, and temporal pole22.As predicted, our results revealed roles for CA1-CA4 and GC-DG, in addition to molecular layer, in the encoding and subsequent retrieval of novel verbal word lists. Several recent studies have provided piecemeal evidence of associations between subfield volumes and verbal episodic memory, implicating subiculum in immediate verbal recallin vivo23 and ex vivo24 results, which have shown age-related decline in CA124 and dentate gyrus/CA4 volumes23. Although we observed some evidence of age-related decline in the IR model for CA1, we note that the GC-DG trend was weaker, and neither CA1 nor GC-DG showed robust decline with age in the DR model. Differences in the segmentation procedures  and our larger sample size likely account for the divergent findings. A notable feature of our present results was the lack of age-related decline for CA2/3 or CA4, whereas volumes of both regions fluctuated with IR and DR performance. Animal models have shown critical roles for dentate gyrus and CA3 in pattern separation and pattern completion respectively, whereby many sources of cortical information are decorrelated in support of discretised memory representations (separation), and where various traces may be combined to allow recall based on multiple representations (completion)49. One implication of our findings may be that pattern completion processes focal to CA2/3 and perhaps CA4 are less susceptible to age-related atrophy in health, whereas regions including subiculum are more prone to manifesting grey matter loss50. Current clinical evidence suggests CA1-CA4 volumes and related recall performance appear to be most heavily impacted in the progression of MCI and Alzheimer’s disease52.A major aim of our present analyses was to explore age-related differences in subfield volumes in tandem with memory performance. That age terms in both the IR and DR models revealed non-linear decline in the volumes of subiculum, molecular layer, and hippocampal tail, differs from existing 26. In particular, the cubic trends noted in our data suggest that poorest performers in IR and DR are likely to manifest subtle tissue loss in subfields including CA2/3, CA4 and GC-DG, compared to average performers. Moreover, it is notable that subfields including CA1 showed fluctuation in volume across IR and DR scores, yet at the upper and lower tails of the IR performance range, CA1 volumes were similar . However, such approaches are restricted to classification of categorical disease outcomes. More recent approaches have involved predicting continuous data  from MRI scans using machine learning methods . Advancing such techniques, recent approaches have trained artificial neural networks to predict cognitive performance based on hippocampal subfield volumes and cortical thickness data57. In future studies, such models could be used to generate predictions for an individual’s expected longitudinal cognitive performance; an observed discrepancy between the model prediction and an individual’s subsequent true performance could serve as a clinical indicator for MCI risk. Moreover, the potential to construct such models using a range of additional physiological measurements as training set features  could enhance prediction accuracy, by allowing for broader characterisation of both neural and physiological phenotypes that may precede MCI onset.Avenues for future research may include the potential to combine detailed assays of hippocampal subfield volumes with advanced machine learning techniques, as a means of predicting cognitive performance based on subfield volumes. Recent machine learning approaches have tracked the progression of MCI towards Alzheimer’s disease  enable the specification of T1w and T2w input images, as aids to hippocampal atlas construction59 or subject-level hippocampal segmentation26. The present imaging protocol did not include a T2w acquisition that was suitable for combined use with the T1w image (owing to in-plane resolution differences); hence, only the T1w image could be used as input to the FreeSurfer segmentation procedure. This holds implications for the accuracy of segmentation of some subfields. As outlined in26, use of T1w images alone in the FreeSurfer parcellation scheme can lead to under segmentation of the molecular layer, an issue that is largely resolved when both T1w and T2w images are used. Thus, future MRI investigations with the TILDA cohort would benefit from integration of high-resolution T1w and T2w scans in order to achieve the most optimal estimates of tissue volumes within the hippocampal subfields.An important consideration for future studies will be scan spatial resolution, which impacts the accuracy of hippocampal subfield measurements; replication of the present results in a cohort with scans of < 0.6 mm isotropic resolution would be beneficial. Indeed, previous investigations have employed higher resolution scans than the present studyIn sum, our results reveal that specific subfields of the hippocampus manifest non-linear associations with verbal memory encoding and retrieval performance in non-demented older adults. These effects are partly dissociable from age-related atrophy, and from naming of well-consolidated semantic categories. Our results may enable us to generate predictions for those at greatest risk of incident memory impairment in future TILDA waves.Supplementary Materials